### 分类： 商业建模代写

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

When we look at the work of Shigeo Shingo about improvement of production processes, he is not talking about processes as such, but rather at process delays. Essentially, he is discussing lossless transitions between (sub)processes and reduction of avoidable waste in transformation (sub)processes [6]. Any storage that is not required for stabilisation of the product is considered a process delay, and as such a loss to be avoided. However, when the period between order and delivery is shorter than the actual time it takes to manufacture a product, stocks are necessary. Therefore, reduction of process delay is key to Shingo’s thinking. Faster production throughput implies less need for stocks, and shifts production from push to pull.

Process improvement is fundamentally about time and timing. Underutilisation of production capacity is allowed when it reduces significantly throughput time. As an example, imagine a production company where the packaging is the bottleneck. The company has to find a balance between order lead time, customer service levels, idle time of expensive packaging equipment, and scrapped stock waiting for orders that did not materialise. Considerations of production cost would argue against investments in equipment, market considerations would argue against higher lead times. Taiichi Ohno writes “In production, ‘waste’ refers to all elements of production that only increase cost without adding value – for example, excess people, inventory, and equipment” [7]. The company will have to balance excess equipment against excess stocks. “Idle equipment” cannot always be equated to “excess equipment”.

To summarise, this kind of process thinking is primarily about pull, flow and avoidance of delays. This requires balancing on both the design level (production capacities) and the operational level (mechanisms for mutual adjustment/modification of production capacities). Processes can be recognised on different aggregation levels. They can be continuous or discrete. To realise flow through processes mechanisms must be in place that prevent unwanted intermediate stocks and unnecessary waiting between (sub)processes.

The relation of a business process to preceding and subsequent processes is another thing. The classic waterfall approach of IT projects is a prototypical example where each subsequent process is triggered by its preceding process and the chain of processes is carried out linearly, without going back to previous processes, until the end result. A second kind of process structure is linear with feedback, either directly feeding information back to a preceding process, or indirectly via some monitoring process. This process structure is found in conventional production companies. A third kind of process structure is with mutual adjustment between preceding and subsequent processes. Here a kind of reciprocity is to be found between preceding and subsequent processes, and this process structure is more likely to be found in production organisations that are based on the lean ideas.

In order to create constant outputs that are useful for customers or internal subsequent processes, business processes must be able to absorb variability. Irregularities in inputs or in the processing that are not absorbed will be passed on as irregularities in outputs.

Often, there will be a trade-off between extra costs caused by eliminating variability in the processes (creating extra consumption of resources. extra waste, and/or late delivery) and the extra costs of not fulfilling specifications and expectations for customers or for subsequent processes. Dealing with such trade-offs might be subject to coordination processes within the company or between the company and its customers.
In the design and execution of business processes there are different dimensions of variability, and different ways for coping with variability. One dimension is quality and deals with specifications and tolerances. Elimination of output variability can be achieved by elimination of variability of input in combination with standardisation of processes (Mintzberg: standardisation of work) [8]. A second way of elimination of output variability is to allow variability of input and have processes in place that eliminate variability in the processes (Mintzberg: standardisation of output). The third option is to allow variability at the output of the process, and then the question is how much the customer or the next internal process can and will tolerate.

Another dimension of variability is quantity and timing. This dimension is about getting the right amount of output at the right time available out of the process, and this requires the right amounts of resources at the right time available for consumption in the process. Some variability will be absorbed in the process. Variability in quantity and time between processes must be resolved by mutual adjustments of the processes, or by rescheduling. Major readjustments will be made dependent on a broad range of competing values. Will a delivery be on time but incomplete, or late and complete? Will an internal process be on time but generate extra costs, or late without extra production costs? This kind of decision making might also depend on the creativity of experienced people. Sometimes people can find smart ways to lessen the negative effects of product or production variability, by balancing requirements and possibilities of efficiency, specifications, timing, and allowable tolerances. Decision making in this kind of adjustment processes requires that a broad range of experience and competence is represented, because (1) heterogeneous values must be weighed against each other and (2) detailed knowledge about processes is needed to evaluate what is really possible in the given situation. And, where the output for customers is affected, both the specific agreement with the customer and the general conventions are important factors in balancing obligations and costs.

Gareth Morgan wrote about the mechanical view on organisations “When we talk about an organisation, we usually have in mind a state of orderly relations between clearly defined parts that have some determinate order. Although the image may not be explicit, we are talking about a set of mechanical relations. We talk about organisations as if they were machines, and as a consequence we tend to expect them to operate as machines: in a routinized, efficient, reliable, and predictable way” [9]. Peter Senge wrote about the machine metaphor something similar: “A machine exists for a purpose conceived of by its builders” and “To be effective, a machine must be controllable by its operators. This, of course, is the raison d’être of management – to control the enterprise” [10]. Such a view on organisations is reflected in the usage of the concept of enterprise engineering, which suggests that a company can be engineered like a machine. The Complete Business Process Handbook defines a business process “as a collection of tasks and activities (business operations and actions) consisting of employees, materials, machines, systems and methods that are being structured in such a way as to design, create, and deliver a product or service to the customer” [11] In the formal BPMN specification of the OMG a business process is defined as “A defined set of business activities that represent the steps required to achieve a business objective. It includes the flow and use of information and resources.” [12] These definitions match pretty good with the OED entry for a machine “An apparatus for applying mechanical power, consisting of a number of interrelated parts, each having a definite function” [1], apart from the application of mechanical power.

Of course, Morgan has offered not only the machine metaphor, but also the metaphors for the organisation as an organism, as a brain, as a culture, as political system, as psychic prison, as flux and transformation, and as domination. Each metaphor helps to see certain aspects of an organisation by comparing typical organisational features with features of the concept of the machine, organism, brain, et cetera. In this sense each metaphor is “true” in the sense that the organisation can be considered to have similar features as a machine. At the same time, the concepts brought together in the metaphor differ in many other respects. Morgan has described this paradox of the metaphor as the phenomenon that the statement “A is $\mathrm{B}$ ” can be both very useful and patently false at the same time. Taken metaphorically, the statement “the organisation is a machine” or “the organisation is an organism” can generate insights in the workings of an organisation as a consequence of the similarities between machine and organisation or between an organism and an organisation.

## 有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 商科代写|商业建模代写Business Modeling代考|Blocking Style with Alethic Violations

The interface supports rules styled as alethic by prohibiting user entry of any data that violates them. Our alethic example from EU-Rent is the rule prohibiting a rental from being open if a driver who is authorized for it is barred [10]. The violation gets displayed when a barred driver is entered on a rental request. The rule is classified as pre-authorized in EU-Rent, which makes it alethic in our mapping from Table $1 .$

This corresponds to invariant rules in Ampersand. Ampersand requires immediate resolution of invariant rules. Selecting a barred person triggers a violation message display (see Fig. 5). The corresponding Ampersand code is:
RULE noBarredDriver :
has driver ;has driver / I [Person] I- -is_barred MESSAGE “A barred person cannot have a car reservation”
Our Semantic Web class for barred persons in our EU-Rent extension code as a subclass of class fresvio:Violation called vioBarred. An OWL restriction infers a vioBarred for open rentals with has_driver properties linking into the BarredPerson class. We can validate the rule by creating an individual as a subclass of BarredPerson and an individual as a subclass of class Car_Movement. When we create a property has_driver for the movement individual to the barred person individual, the movement individual is inferred as an instance of class vioBarred, a subclass of fresvio:Violation. By changing the individual to class Person, the individual is no longer in the violation class. The code is:
:vioBarred owl:equivalentClass rdfs:subClassof fresvio:Violation ; $\begin{array}{ll}\text { [ owl:intersectionof } & \text { EURent:Car_Movement } \ \text { [ rdf:type } & \text { owl:Restriction ; } \ \text { owl:onProperty } & \text { EURent:has driver ; } \ \text { owl:allValuesFrom } & \text { EURent:BarredPerson ] ) ] ; } \ \text { :message “A barred person cannot reserve a car”. }\end{array}$

According to the OED [1], a process is “A continuous and regular action or succession of actions, taking place or carried on in a definite manner, and leading to the accomplishment of some result; a continuous operation or series of operations. (The chief current sense.)”. Accordingly, business processes would be about getting business results for customers or about getting internal intermediate results that contribute to the end results, in an effective and efficient way. That is the bottom line. Both effectiveness (getting the right results) and efficiency (consumptions of resources for getting the results) are important issues in the executing of the business processes. The final result of the primary processes would deliver a product or service for the customer outside the company. The internal intermediate results would yield either intermediate semifinished products or provide information or material for executing and controlling processes.

John Kay wrote about the foundations of neo-classical economics as “The ArrowDebreu results are the culmination of a long tradition in economics which emphasises supply and demand, perfectly competitive markets and the search for market equilibrium, conducted by independent, self-regarding agents. This framework is today known as “neo-classical economics” [2] and “there is no escaping the fundamental theorems of welfare economics if we are to examine the claim that competitive markets necessarily lead to efficient outcomes”. This idealised view on doing business on markets is still dominant today. Economic exchanges are in this view considered to be fully specified, instantaneous events on markets. The essential assumptions of this dominant views are criticised since many years. Ronald Coase asked in 1937 the fundamental question “why a firm emerges at all in a specialised exchange economy” [3]. If the market would provide the best mechanism for coordination and optimisation of economic exchanges, then each human individual would be best off by being an autonomous independent actor on the market. By what right would a firm exist? His analysis was that classical economics neglected transaction costs, resources that are consumed in order (1) to find the best transaction, (2) to do the transaction, and (3) to enforce the transaction. Therefore, his answer was that the rationale for a firm was the reduction of transaction costs by organising economic activities in a hierarchical organisation.
As a scholar of law Ian MacNeil analysed classical contract law and its assumptions about business exchanges [4]. He found that classical contract law assumes atomic and fully specified exchanges, and by examining the objective facts a court is to decide if the terms of the contractual exchange were fulfilled, or not. However, by studying business contracts in practice he found that business practices are mostly relational by nature. A written business contract is secondary to a business agreement. The agreement between business parties is about promising future performance under circumstances that might not be fully known at the time of the agreement, and a business contract is an imperfect written representation of the agreement. The business parties will expect the agreement to be fulfilled, when one of the partners is disappointed in the other’s behaviour this will hamper or preclude future business. MacNeil identified five basic elements of contract: (1) co-operation; (2) economic exchange; (3) planning for the future; (4) potential external sanctions; and (5) social control and manipulation. Cooperation is about trust, sanctions and/or social control are about enforcement of the agreement. Legal sanctions based on the written contract are mostly a means of last resort. Even in such cases the court will have to look not only at the letter of the contract but will also consider the context and conventions in business. From an economical point of view, this social practice of business agreements based on promises, expectations, trust and a mix of social and legal sanctions is efficient. Relying only on fully specified and legally watertight contracts (if possible) would force up transaction costs hugely, and this would imply a huge competitive disadvantage.

## 商科代写|商业建模代写Business Modeling代考|Blocking Style with Alethic Violations

RULE noBarredDriver :
has driver ;has driver / I [Person] I- -is_barred MESSAGE “A barred person cannot have a car reservation”

:vioBarred owl:equivalentClass rdfs:subClassof fresvio:Violation ; [猫头鹰：交集  EURent:Car_Movement   [ rdf：类型  猫头鹰：限制；   猫头鹰：onProperty  EURent：有司机；   猫头鹰：allValuesFrom  EURent:BarredPerson ] ) ] ;   :message “被禁止的人不能预订汽车”。

John Kay 在谈到新古典经济学的基础时写道：“ArrowDebreu 的结果是经济学长期传统的结晶，它强调供求关系、完全竞争的市场以及由独立、自私的代理人进行的对市场均衡的探索。这个框架今天被称为“新古典经济学”[2]，并且“如果我们要研究竞争市场必然导致有效结果的主张，就无法逃避福利经济学的基本定理”。这种在市场上开展业务的理想化观点今天仍然占主导地位。在这种观点中，经济交易被认为是市场上完全具体的、即时的事件。这种主流观点的基本假设多年来一直受到批评。罗纳德·科斯 (Ronald Coase) 在 1937 年提出了一个基本问题“为什么公司会出现在专门的交换经济中”[3]。如果市场能够为经济交易的协调和优化提供最佳机制，那么每个人都将成为市场上自主独立的参与者。一家公司凭什么存在？他的分析是，古典经济学忽略了交易成本，即为了（1）找到最佳交易、（2）进行交易和（3）执行交易而消耗的资源。因此，他的回答是，公司的基本原理是通过在等级组织中组织经济活动来降低交易成本。如果市场能够为经济交换的协调和优化提供最佳机制，那么每个人都将成为市场上自主独立的参与者。一家公司凭什么存在？他的分析是，古典经济学忽略了交易成本，即为了（1）找到最佳交易、（2）进行交易和（3）执行交易而消耗的资源。因此，他的回答是，公司的基本原理是通过在等级组织中组织经济活动来降低交易成本。如果市场能够为经济交换的协调和优化提供最佳机制，那么每个人都将成为市场上自主独立的参与者。一家公司凭什么存在？他的分析是，古典经济学忽略了交易成本，即为了（1）找到最佳交易、（2）进行交易和（3）执行交易而消耗的资源。因此，他的回答是，公司的基本原理是通过在等级组织中组织经济活动来降低交易成本。按顺序消耗的资源 (1) 找到最佳事务，(2) 执行事务，以及 (3) 执行事务。因此，他的回答是，公司的基本原理是通过在等级组织中组织经济活动来降低交易成本。按顺序消耗的资源 (1) 找到最佳事务，(2) 执行事务，以及 (3) 执行事务。因此，他的回答是，公司的基本原理是通过在等级组织中组织经济活动来降低交易成本。

## 有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

We consider rule expressions defined in relation algebra as a starting point for determining rule styles. We create an ontology for business rules that contains the necessary components to be displayed in the interface. The focus is on how the mapped business rules can be displayed in the interface. The Ampersand tool [6] displays errors directly when detecting business rule violations. The rule modality determines whether the user may or may not proceed without resolving the violation. If the user may proceed, a violation message appears in a yellow box as a warning. If the violation may not even be temporary, then the message box is red.

Ampersand classifies rules by the method of enforcement, which can be an axiom, invariant rule, process rule or automated rule [6]. The syntax of a rule in Ampersand contains a purpose, meaning, message, violation text and expression of the rule in relation algebra. The purpose and meaning are used to inform the end user why a rule exists and what it means. The message and violation text contain information to be displayed on screen when the rule is violated. The violation text can contain references to the concepts and relations that cause the violation, whereas the message informs the user without explicitly mentioning the affected instance. We use the message of a rule in our research for displaying rule violations. For process and automated rules, a role is defined that should maintain the business rule.

Another Ampersand feature is limiting input values to a composition of relations. This feature prevents users from selecting values that would trigger a violation. While Ampersand displays violations on screen, it does not change the style of a field when a rule states that this field should be mandatory. The limitation of input values for an input field based on a composition of relations must be configured separately, as the composition is not derived from business rules specified by a business engineer. In earlier work, we use Ampersand to demonstrate how relation algebra implementations of business rules apply to IT alignment [4].

Fresnel displays RDF data in a human readable form on semantic browsers [11]. CSS [1] has a significant influence on Fresnel: CSS does for XML and HTML what Fresnel does for RDF. For example, the CSS concepts of selectors and the formatting model are also important to Fresnel. A CSS selector specifies components of XML and HTML documents so it can apply a given style to them. The formatting model for CSS is the HTML document display, with familiar document structure components such as paragraphs, along with a more abstract box model. A CSS rule has a selector and a style declaration. A CSS declaration can say which type of formatting model component the selected document content appears in. A CSS declaration also defines the more familiar aspects of CSS visual style for selected content, such as font size.

While CSS has its own syntax, Fresnel code consists of RDF triples, which conform to the RDFS-defined ontology for Fresnel. Fresnel has two main concepts: lenses and formats, both of which correspond roughly to the CSS rule. Lenses determine which properties of RDF (Resource Description Format) data to show and in what order. Formats determine how to display, typically using CSS.

The remaining sections evaluate our proposed model for rule styles by demonstration. We implement business rules retrieved from $E U$-Rent [10]. Our prototype uses and, where needed, extends an OWL-defined ontology for EU-Rent [12] and an Ampersand implementation for EU-Rent [5]. Each demonstration has this structure:

• Explanation of the rule and desired behavior of the rule style
• Demonstration in Ampersand
• Encoding in the Semantic Web
• Proposed Fresnel implementation
• Example of the rule style output in Semantic MediaWiki.
Our ontology for alethic and deontic business rules is derived from how Ampersand captures business rules with the rule syntax [6]. We made the rule types in our ontology explicit as OWL restrictions. The ontology can be extended with additional subclasses and properties relevant for each rule type. A business rule is created as subclass of a new general violation class. The rules contain class restrictions modelled as equivalent classes that are asserted by as style in Fresnel with Fresnel Violations. A property for the violation message of the business rules captures the message to be displayed for the violation.

The message annotation is also similar in Ampersand. The main difference is that Ampersand can also integrate classes and properties (or concepts and relations) in the message using the keyword VIOLATION, whereas our message is an annotation property that only contains text. A comparison of syntax used in Ampersand and our Violation ontology is listed in Table 2. This paper’s code fragments use bold font to emphasis specific aspects in the syntax of the various languages. In Ampersand, bold font indicates where the logic is defined, while the rest is names and strings. The Fresnel code fragments have our own extensions displayed in bold.

This paper’s Semantic Web definitions of this same type of rule are usually as OWL equivalent classes of OWL restrictions, as the code fragments in the upcoming sections show. Items that violate of the rule get inferred as an instance of the rule’s assigned class. The benefit of using this method is that is guides exchange of rule expressions between relation algebra and OWL, provided that the RDFS classes and properties have equivalents in the concepts and relations in Ampersand. In each demonstration, we show Semantic Web code. We use bold font for URLs that we make, either as extensions to existing ontologies, or as our own example triples. The restriction that determines whether an instance will be inferred is listed under the header equivalent class. Constructs that the Violation ontology introduces have the namespace prefix “fresvio:”.

This section’s implementation shows a list of violations of the EU-Rent rule that prohibits a rental period from exceeding 90 days. While an alethic rule would prevent any initial car rental reservation from lasting more than 90 days, one can extend reservations during rental, and renters can return cars late. Therefore, an open car rental can become overdue and thus trigger a rule violation. Process lists inform the user of this kind of rule violation. Since neither relation algebra nor the Semantic Web perform math, we simply add a data property to the RDFS ontology code, and a relation in relation algebra representation, each of which indicate overextended rentals. For Ampersand, an example for computing the maximum rental days is made [5].

This rule is post-justified, and thus deontic, and similar to the process rule in Ampersand. The Ampersand tool displays existing process rule violations as a list (see Fig. 3). Clicking on the warning message shows the elements causing the violation. Clicking on one presents a form to amend information about the element. This can be viewed as a process list. The rule in Ampersand is expressed as follows:
RULE max90Days : I [Carmovement] I- -longerthang0days
MESSAGE
“There are car rentals open for more than 90 days”
As before, we define this on the Semantic Web as an OWL restriction. A data property states whether the car movement exceeds the 90 -day maximum. We verify the rule with an example with a Car Movement individual whose property isOverdue is true, which then infers it as a CarMovementopenoverdue.

Our goal is to show all instances of class CarMovementopenoverdue in a table overview, similar to how Ampersand displays a process list. Our Fresnel code defines a

lens that selects the URL for the class. This lens displays the message and then all objects linked by the inverse property for rdf : type, which thus infers all movements violating this rule. The Fresnel lens code is:
vioRent:CarMovementopenoverduelns a fresnel: Lens ; fresnel:instanceLensDomain $\quad$ VioRent: CarMovementopenOverdue ; fresnel:purpose fresnel:defaultLens; fresnel: showProperties $\quad$ ( fresvio:message fresvio:hasinstance ) .

## 商业建模代考

＆符号通过执行方法对规则进行分类，可以是公理、不变规则、过程规则或自动规则[6]。Ampersand 中规则的语法包含关系代数中规则的目的、含义、消息、违规文本和表达式。目的和含义用于告知最终用户规则存在的原因及其含义。消息和违规文本包含违反规则时要在屏幕上显示的信息。违规文本可以包含对导致违规的概念和关系的引用，而消息会通知用户而没有明确提及受影响的实例。我们在研究中使用规则信息来显示违反规则的情况。对于流程和自动化规则，定义了一个应该维护业务规则的角色。

Fresnel 在语义浏览器 [11] 上以人类可读的形式显示 RDF 数据。CSS [1] 对 Fresnel 有重大影响：CSS 对 XML 和 HTML 的作用就像 Fresnel 对 RDF 的作用一样。例如，选择器的 CSS 概念和格式化模型对 Fresnel 也很重要。CSS 选择器指定 XML 和 HTML 文档的组件，因此它可以将给定的样式应用于它们。CSS 的格式化模型是 HTML 文档显示，具有熟悉的文档结构组件（例如段落）以及更抽象的框模型。CSS 规则有一个选择器和一个样式声明。CSS 声明可以说明所选文档内容出现在哪种类型的格式化模型组件中。CSS 声明还定义了所选内容的 CSS 视觉样式更熟悉的方面，例如字体大小。

• 规则说明和规则样式的期望行为
• & 符号中的演示
• 语义网中的编码
• 建议的菲涅耳实施
• Semantic MediaWiki 中的规则样式输出示例。
我们的 alethic 和 deontic 业务规则本体源自 Ampersand 如何使用规则语法 [6] 捕获业务规则。我们将本体中的规则类型明确表示为 OWL 限制。可以使用与每个规则类型相关的附加子类和属性来扩展本体。业务规则被创建为新的一般违规类的子类。规则包含建模为等效类的类限制，这些类限制在 Fresnel with Fresnel Violations 中由 as 样式声明。业务规则的违规消息的属性捕获要为违规显示的消息。

Ampersand 中的消息注释也类似。主要区别在于，Ampersand 还可以使用关键字 VIOLATION 在消息中集成类和属性（或概念和关系），而我们的消息是仅包含文本的注释属性。表 2 中列出了 Ampersand 和我们的 Violation 本体中使用的语法比较。本文的代码片段使用粗体字来强调各种语言语法中的特定方面。在与符号中，粗体表示逻辑的定义位置，其余的是名称和字符串。菲涅耳代码片段有我们自己的扩展，以粗体显示。

RULE max90Days : I [Carmovement] I- -longerthang0days
MESSAGE
“有租车营业时间超过 90 天”

vioRent:CarMovementopenoverduelns a fresnel: Lens ；菲涅耳：instanceLensDomainVioRent: CarMovementopenOverdue ; 菲涅尔：目的菲涅尔：defaultLens；菲涅尔：showProperties（fresvio：消息fresvio：hasinstance）。

## 有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 商科代写|商业建模代写Business Modeling代考|Using Audit Tools to Find and Correct Errors

When inheriting a model, there are several factors to come to grips with: the layout, design, formatting, assumptions, and formulas. Of all these, following the formula calculations is the most difficult, and verifying and validating formulas can be very time-consuming. The fastest way to understand a formula when you see it for the first time is to go into Edit mode. Double-click a cell, or select it and press F2. If the formula’s source inputs are on the same page, they’ll show visually where the source data is coming from that feeds the cell calculation, as shown in Figure 5-5. The color codes are helpful; each range in the formula will be the same color as the highlight source data that feeds it. If you’d like to try this out for yourself, download File $0501 . x l s x$ from www. dummies.com/go/financial model inginexcel fd2e. Open it and select the tab labeled $5-5$.When you’re in Edit mode and you decide that you need to change the range the formula is referring to, you can use the mouse to click and drag the colored lines to reference a different cell. For example, in Figure $5-5$ if you want the range B3:B12 to be A3:A12 instead, click the colored line showing between the A and B column and drag it so that the cell reference is column A instead of column B.

On the Formulas tab in the Ribbon, there is a formula auditing section that contains a number of tools that you’ll find useful when trying to understand someone else’s financial model. Just remember that using these audit tools in Excel is not the same as performing a formal financial model audit.

A formal financial model audit is a very detailed process in which a model auditing team takes the model apart and checks it meticulously for errors. If the bank is lending you money based on the results of the financial model, one of the conditions of the loan might be that the model be audited to make sure that the results can be relied upon. Getting a model professionally audited can be an extremely expensive undertaking, but it’s really the only way to ensure that there are no errors. Note that a financial model audit is sometimes called a model review to differentiate it from a financial audit.

Of course, creating your own financial model is a lot more interesting than checking someone else’s. But Excel’s audit tools make checking someone else’s model somewhat easier. Formula errors are the most common type of error in financial models, and the audit tools exist almost solely for the purpose of finding these formula errors.

## 商科代写|商业建模代写Business Modeling代考|Checking a model for accuracy

The formula auditing tools can help get to the root of what’s causing the error in a cell through tracing relationships among cells within your worksheet. These tools will help you find the source of an error, but they’ll also, more importantly, help you find an error you didn’t know was there. By tracing the relationships, formula auditing lets you test formulas to see the precedents (cells that directly supply the formulas) and the dependents (the cells that depend on the results of the formulas). Excel also offers a way to visually reverse any potential sources of an error in the formula of any particular cell.

The formula auditing tools can be found in the command buttons located in the Formula Auditing group on the Formulas tab of the Ribbon. These command buttons include the following:

) Trace Precedents/Trace Dependents: In trying to understand a model, you’ll spend the majority of your time working through the formulas and making sure you understand exactly how each output has been calculated. Trace Precedents and Trace Dependents are good places to start when you’re trying to see where the cell links are coming from and going to. These tools are helpful to identify the linkages that exist between the cells and display the relationships visually with blue tracer line arrows.To use Trace Precedents, start with an output cell that contains a formula you want to understand, such as the formula in cell G26 in Figure 5-6. Select the cell and click the Trace Precedents button in the Formula Auditing section of the Formulas tab. This displays blue tracer line arrows, which show which cells G26 depends on.

Mixed cell referencing is a combination of relative and absolute referencing; one part of the reference is absolute, and the other is relative. When you add a dollar sign before the row, the row remains anchored when the cell is copied; when you add a dollar sign before the column, the column remains anchored when the cell is copied.

For example, if you create the reference =B2 in a cell, and then copy that reference down, it will change to $B 3$. If you add some anchoring, here are the results in each case:
\begin{tabular}{l|l}
Cell & Copies as Cell \
\hline$=\mathrm{B} 2$ & $=\mathrm{B} 3$ \
\hline$=\$ \mathrm{~B} \$2$ & $=\$ \mathrm{~B} \$2$ \
\hline$=\mathrm{B} \$ 2$&$=\mathrm{B} \$2$ \
\hline$=\$ \mathrm{~B} 2$&$=\$\mathrm{~B} 3$
\end{tabular}
The dollar sign anchors a row number or column letter when you copy it. You can anchor both the column and the row (absolute referencing), or you can anchor one or the other (mixed referencing).

Mixed cell referencing is a concept critical to good financial modeling practice, so it’s important for a financial modeler to understand this fundamental concept. Used effectively, mixed cell references make your model

Faster to build and more efficient
3) Less prone to error
3) Quicker, easier, and cheaper to audit
The easiest way to quickly add absolute and mixed cell referencing is to press F4 immediately after adding the reference to the formula. This keyboard shortcut cycles through combinations of relative and absolute referencing. You can repeatedly press F4 after entering the cell name in a formula to cycle through the mixed references. For example, type $=\mathrm{B} 2$ and then press $\mathrm{F} 4$ to display $=\$ \mathrm{~B} \$2$. Press $\mathrm{F} 4$ again to display $=8 \$ 2$. Press$\mathrm{F} 4$again to display$=\$82$. And press $\mathrm{F} 4$ again to display $=B 2 .$

Let’s look at a practical example of how to use mixed cell referencing. In the following example, you want to calculate how much you’d receive in interest under three different portfolio amounts and three different interest rates. The most efficient way to perform this calculation is to create a single formula with appropriate references and then copy that formula to other cells. You need to create a formula that multiplies the interest amount in row 1 and the borrowing amount in column A.

Instead of creating nine different formulas, you’re creating only one single formula using mixed cell referencing, which you can then copy across, saving you time and reducing the possibility of error.

## 商科代写|商业建模代写Business Modeling代考|Checking a model for accuracy

) Trace Precedents/Trace Dependents：在尝试理解模型时，您将花费大部分时间研究公式并确保您准确了解每个输出是如何计算的。当您尝试查看单元格链接的来源和去向时，跟踪先例和跟踪依赖项是很好的起点。这些工具有助于识别单元格之间存在的联系，并使用蓝色跟踪线箭头直观地显示关系。要使用跟踪先例，请从包含您想要理解的公式的输出单元格开始，例如单元格 G26 中的公式在图 5-6 中。选择单元格并单击“公式”选项卡的“公式审核”部分中的“跟踪先例”按钮。这将显示蓝色示踪线箭头，显示 G26 所依赖的单元格。

\begin{tabular}{l|l} 单元格并复制为单元格 \\hline$=\mathrm{B}2$ & $=\mathrm{B}3$\\hline$=\$\mathrm{~B} \$2$&$=\$\mathrm{~B}\$2$\\mathrm{B}\$2$&$=\mathrm{B}\$2$\\hline$= \$\mathrm{~B} 2$ & $=\$\mathrm{~B}3$\end{表格}\begin{tabular}{l|l} 单元格并复制为单元格 \\hline$=\mathrm{B}2$&$=\mathrm{B}3$\\hline$=\$\mathrm{~B} \$2$&$=\$\mathrm{~B}\$2$\\mathrm{B}\$2$&$=\mathrm{B}\$2$\\hline$= \$\mathrm{~B} 2$&$=\$\mathrm{~B}3$\end{表格}

3) 更不容易出错
3) 审核更快、更容易、更便宜

## 有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

## 商科代写|商业建模代写Business Modeling代考|Using Someone Else’s Financial Model

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 商科代写|商业建模代写Business Modeling代考|Why templates can be appealing

If you describe yourself as a “casual” financial modeler, your usual job might be something else entirely, but part of your professional and personal life means that you need to create a budget or financial statements, or maybe just do some pricing calculations. If this is you, you’re probably looking for an easy way to create a quick financial model that gives you the results you need. Starting to build a full financial model entirely from the ground up, especially when you have no idea where to begin, can be rather daunting. Using a template is a very appealing option because it requires a much lower initial investment of time and money than building a model yourself.

If the business or situation you’re trying to model is extremely simple and/or your business is exactly the same as every other business, you’ll be fine with a template. However, most templates are really just a nicely formatted spreadsheet. There is a bit more to building a robust, responsive, and accurate financial model than plugging a few numbers into a spreadsheet.

If you’re looking for a shortcut to building a financial model, keep in mind what a fully functional, dynamic model does that a basic spreadsheet does not. For more information about differentiating a model from a spreadsheet, turn to Chapter $1 .$

## 商科代写|商业建模代写Business Modeling代考|What’s wrong with using templates

When you’re first starting out, a template may be a good way to get going. But think of a template as a car with no engine – it looks great on the surface, but there’s no performance! Here are a few important features you won’t have when you use a template:

Financial models need drivers: What makes a really good financial model is its ability to take the business model and represent it financially. Revenues and expenses don’t just happen – something occurs that makes that revenue

or expense become a reality. Drivers are absolutely critical in creating a financial model that is flexible and scalable. For example, if you were to achieve 10 percent market penetration, and your product was priced at $\$ 5$, your revenue would be, say,$\$100,000$ per month. Many templates simply show a hard-coded value of $\$ 100,000$for revenue, but in your model, you need to know exactly what had to happen in order for revenue to be calculated at$\$100,000$.

Of course, the beauty of this method not only means that investors or other users can trace back to see how the revenue is calculated, but you can also run scenarios and sensitivity analyses on these inputs. What if penetration were 12 percent? What if you decreased the pricing by 10 percent? This sort of analysis is virtually impossible with a simple input of $\$ 100,000$for revenue. 3) Customized inputs: A fill-in-the-blanks template has to suit everyone, so in order to meet the requirements of virtually any business model, the inputs must be kept generic (Revenue Item 1, Revenue Item 2, and so on). Of course, you can change the titles of these line items, but what if you have different lines of businesses that need to be separated? Here’s another example: “Office Rent” – a line item often found in a template – may not apply to your company. Maybe you bought your building, have a mortgage (a liability, not an expense), and need a way to factor in the mortgage pay down and interest portion of each payment. An experienced financial modeler would have no problem working this into a customized forecast. If you’re using a template, you’ll have a hard time getting the template to meet your needs. Plus, you’ll probably spend more time manipulating the template to meet your needs than you would’ve spent just building it from scratch. Scalability: Just like that cheap one-size-fits-all shirt you bought from the market, your model will probably never fit properly. It’s pretty much guaranteed that whatever number of inputs the template designer has chosen won’t be exactly what you need. Inserting or deleting rows may seem simple, but any Excel modeler knows how deadly that can be. Before you know it, you’ve ended up with a model full of dreaded #REF! errors. To avoid this, the template designer likely created a large number of unnecessary rows and columns just in case you need them. Most templates contain a huge amount of redundant information and unnecessary complexity, which is confusing, takes up memory, and is simply poor modeling practice. Specialized functionality: The standard financial reports have always been the balance sheet, cash flow statement, and income statement, but there are many additional reports that might be useful to your business but not necessarily to others. Unfortunately, you won’t find anything beyond standard, minimum functionality in a template. ## 商科代写|商业建模代写Business Modeling代考|Why you should build your own model Imagine you are working on the due diligence for a potential acquisition by your company of a smaller one. Someone else created a model to project the financials but has since left the company, and you’re responsible for the financial model now. Your investor asks why your sales projections increase so sharply when the expenses do not. The answer – “because that’s what the financial model says” is simply not good enough. If you’re responsible for the model, you need to be familiar enough to able to answer a question like that – perhaps not off the top of your head, but you should be able to understand the drivers of the model to provide a timely and insightful answer to these kinds of questions. Blindly accepting the output of a model is foolish and extremely dangerous. Learning from other people’s models is often helpful, but it’s rarely efficient to build a model using their templates. Trying to change things becomes difficult when a formula doesn’t change in the way you expect it to, and a nuance will come back to haunt you because you didn’t understand the financial model to begin with. You may think that a template will help you save time, but in the long run, it will end up costing you more time and lead to potential error. Although building your own model can be time-consuming, you’ll no doubt be far more comfortable with the results. Not only will you be able to vouch for the accuracy of the calculations, but during the model-building process you’ll improve your modeling and Excel skills and your understanding of the business. ## 商业建模代考 ## 商科代写|商业建模代写Business Modeling代考|Why templates can be appealing 如果您将自己描述为“休闲”财务建模师，那么您通常的工作可能完全是另一回事，但您的职业和个人生活的一部分意味着您需要创建预算或财务报表，或者可能只是进行一些定价计算。如果这是您，您可能正在寻找一种简单的方法来创建快速财务模型，从而为您提供所需的结果。完全从头开始构建完整的财务模型，尤其是当您不知道从哪里开始时，可​​能会相当艰巨。使用模板是一个非常有吸引力的选择，因为与自己构建模型相比，它需要的时间和金钱的初始投资要少得多。 如果您尝试建模的业务或情况非常简单和/或您的业务与其他所有业务完全相同，那么您可以使用模板。但是，大多数模板实际上只是格式精美的电子表格。建立一个稳健、响应迅速且准确的财务模型比将一些数字插入电子表格还需要更多的东西。 如果您正在寻找构建财务模型的捷径，请记住功能齐全的动态模型能做什么，而基本电子表格却不能。有关将模型与电子表格区分开来的更多信息，请参阅章节1. ## 商科代写|商业建模代写Business Modeling代考|What’s wrong with using templates 当您第一次开始时，模板可能是一个很好的开始方式。但是把模板想象成一辆没有引擎的汽车——表面上看起来很棒，但没有性能！以下是您在使用模板时不会拥有的一些重要功能： 财务模型需要驱动因素：真正优秀的财务模型是其采用商业模型并在财务上代表它的能力。收入和支出不只是发生 – 发生的事情使收入 或费用成为现实。驱动因素对于创建灵活且可扩展的财务模型至关重要。例如，如果您要实现 10% 的市场渗透率，并且您的产品定价为$5，您的收入将是，例如，$100,000每月。许多模板只是显示一个硬编码的值$100,000对于收入，但在您的模型中，您需要确切知道必须发生什么才能计算收入$100,000. 当然，这种方法的美妙之处不仅在于投资者或其他用户可以追溯以查看收入是如何计算的，而且您还可以对这些输入进行情景和敏感性分析。如果渗透率为 12% 会怎样？如果您将价格降低 10% 会怎样？这种分析几乎不可能通过简单的输入$100,000为收入。
3) 自定义输入：填空模板必须适合每个人，因此为了满足几乎任何业务模型的要求，输入必须保持通用（收入项目 1、收入项目 2，等等）。当然，您可以更改这些订单项的标题，但如果您有不同的业务线需要分开怎么办？

## 有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 商科代写|商业建模代写Business Modeling代考|Build in Error Checks

Even if you’ve only just started modeling, you’re probably well aware how easy it is to make a mistake in a financial model! There are three ways to prevent errors in a financial model:

Avoid making the mistake in the first place. In this book, I describe several techniques that you can employ to avoid making mistakes in the first place, such as being consistent with your formulas.
$\boldsymbol{\gg}$ Check the model for errors. Despite your best efforts, errors will almost inevitably slip through, so check, double-check, and have someone else check your model after it’s complete.
Include error checks. As you’re building the model, include error checks that prevent inadvertent errors from slipping into the model due to incorrect entries, calculations, or user error.
For more examples of different types of commonly made mistakes, and some ways to avoid making these errors in your models, see Chapter 13. This section focuses on the first two points: techniques for model building to reduce error, as well as ways to check the model for errors.

Error checks are a critical part of a well-built financial model so that the user or modeler can see at a glance if the formulas are calculating correctly. For example, when creating management reports, check that the sum of each individual department’s report adds to the company-wide total. This can be done by inserting a simple IF function, among other methods.

## 商科代写|商业建模代写Business Modeling代考|Allowing tolerance for error

=我F(D17≺>R17, “错误”, 0)是一种高级错误检查，但它有时会返回错误的错误结果，即使值看起来相同。（有关如何在这样的公式中使用 IF 语句，请参阅第 7 章。）这个“错误”是由于 Excel 将计算保留到小数点后 14 位造成的。之后，Excel会截断值，这会导致微小的差异，这会导致公式在差异很小时报错0.00000000000001离开。为避免错误检查的可能性，请使用以下方法之一：
s) 根据非零容差测试差异的绝对值。例如=如果⁡(ABS⁡(D17−R17)>1, “error”, 0 ) 将允许值在报告错误之前相差 1。您应该使用 Excel 的 ABS 函数，该函数将获取结果的绝对值，因此无论是正差还是负差都没有关系。

) 使用公式测试差异的舍入值是否非零=如果⁡(圆形的⁡(D17−R17,0)=0,0， “错误”)反而。

## 有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

## 商科代写|商业建模代写Business Modeling代考|Building a Financial Model by the Rulebook

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

The term “garbage in, garbage out” is never truer than in relation to financial modeling. You can have the most beautifully laid-out financial model with perfect formatting, a great design, and fabulous-looking charts and scenario tables, but if the inputs are not trusted, the model is effectively useless and no one will use the outputs. Important decisions are made based on the outputs of financial models, so listing the assumptions that have gone into the model is critical.

Documentation of assumptions is certainly not the most exciting part of financial modeling, so you may be tempted to leave it to the end. Don’t fall into this trap! When you’re done building your model, you won’t remember the source or reasoning for the assumptions. Document as you go. Whenever you make a structural change or even a minor change to one of the inputs, document it, even if it seems unimportant at the time.

List assumptions on a separate page, and label them clearly, so that they can be easily identified and referenced at a glance. For a small model, you may decide to mix source data and assumptions together. In a large model, you may separate them with as much detail as is possible or practical. For a detailed model, you may list every assumption on a dedicated sheet and then summarize the important ones on a separate sheet. Think about the level of detail in your model, and let that guide the detail of your documentation of assumptions.

Still not convinced that documenting assumptions is important? How’s this for persuasion: When you move to another role or you are away (hopefully, on vacation!), and something goes wrong with the model, who do you think they’re going to blame? You guessed it! Think of documenting assumptions as covering your butt. Your model needs to be able to speak for you when you aren’t around to explain or defend your work. The documentation of assumptions should explain your thought process and potentially also why the model is built the way it is. That way, if there are any questions as to the structure of the model, the approach to certain formulas or the assumptions, they can be easily explained by the model itself.

## 有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

If other people are going to be using your model, be sure to explain the assumptions you made in building the model, especially if the person who is going to be using your model is not an experienced modeler. Users tend to put blind faith in the outcome of the model, which can be dangerous. Instead of taking the model results as gospel, the user should simply use them as a guide.

Models are only a construct that reflects reality; they are not reality. You can make this clear to users of the model by using language such as “Based on our forecasts … ” or “Assuming trends continue….”

In the example of the decision analysis model for the bus company case study (see the section “Identifying the Problem That Your Financial Model Needs to Solve,” earlier in this chapter), the builder of this model might say, “We’re going to lose half of our profit over the next 12 months,” which is not incorrect, but it would be more accurate to say, “Based on current forecasts, we’re going to lose half of our profit over the next 12 months unless we take action” and then show the inputs and assumptions used. For example, the modeler is assuming the following:
3) Five hundred tickets will be sold in the first month of operation.
3) Ticket sales will increase by $1.5$ percent per month after the first month.

) There is no cannibalization between the routes. Often, when launching a new product, some existing customers switch to the new product. Because the new route is servicing a new area, the modeler doesn’t expect any cannibalization and hasn’t included it in this model.

When designing the layout of a model, most experienced modelers follow these rules:

Separate inputs, calculations, and results, where possible. Clearly label which sections of the model contain inputs, calculations, and results. You can put them on separate worksheets or separate places on one worksheet, but make sure that the user knows exactly what each section is for. Color coding can help with ensuring that each section is clearly defined.
) Use each column for the same purpose. This is particularly important when building models involving time series. For example, in a time-series model, knowing that labels are in column B, unit data in column C, constant values in column $D$, and calculations in column $E$, makes it much easier when editing a formula manually.
) Use one formula per row or column. This forms the basis of the bestpractice principle whereby formulas are kept consistent using absolute, relative, and mixed referencing, as described in greater detail in Chapter 4 . Keep formulas consistent when in a block of data, and never change a formula halfway through.
Refer to the left and above. The model should read logically, like a book, meaning that it should be read from left to right and top to bottom. Calculations, inputs, and outputs should flow logically to avoid circular referencing. Be aware that there are times when left-to-right or top-to-bottom data flow can conflict somewhat with ease of use and presentation, so use common sense when designing the layout. By following this practice, you can

avoid having calculations link all over the sheet, which makes it harder to check and update. Excel will also calculate more quickly if you build formulas in this way because it calculates left to right, and top to bottom, so not only does it make your model easier to follow, it will calculate more efficiently.
3) Use multiple worksheets. Avoid the temptation to put everything on one sheet. Especially when blocks of calculations are the same, use separate sheets for those that must be repeated to avoid the need to scroll across the screen.

) Include documentation sheets. A documentation sheet where assumptions and source data are clearly laid out is a critical part of any financial model. A cover sheet should not be confused with an assumptions sheet. A model can never have too much documentation!

## 商科代写|商业建模代写Business Modeling代考|Defining inputs, calculations, and output blocks

Typically, modelers work from back to front when building their models. The output, or the part they want the viewer or user to see, is at the front, calculations are in the middle, and source data and assumptions are at the back. Like the executive summary, a board paper, or another report, the first few pages should contain what casual viewers need to see at a glance. If they need further information, they can dig deeper into the model.

Here are some guidelines of what might be included on each tab in your model:
\$Cover sheet: Although not always included, the cover sheet contains many details about the model. Of course, the cover sheet is not much use unless you keep it up to date. If you decide to include a cover sheet, you may add details such as the following: • A log of changes and updates to the model with date, author, change details, and their impact on the output of the model, which can help with version control • The purpose of the model and how it is intended to be used going forward • Who originally wrote the model and who to contact with questions • Table of contents • Instructions on how to use the model • Disclaimers as to the limitations of the model, legal liability, and caveats • Global or key assumptions integral to the use of the model ## 商业建模代考 ## 商科代写|商业建模代写Business Modeling代考|Documenting the Limitations of Your Model 如果其他人将使用您的模型，请务必解释您在构建模型时所做的假设，特别是如果将使用您的模型的人不是经验丰富的建模者。用户倾向于盲目相信模型的结果，这可能很危险。用户不应将模型结果视为福音，而应简单地将它们用作指南。 模型只是反映现实的结构；它们不是现实。您可以使用诸如“基于我们的预测……”或“假设趋势继续……”之类的语言向模型的用户说明这一点。 在公交公司案例研究的决策分析模型示例中（参见本章前面的“确定您的财务模型需要解决的问题”部分），该模型的构建者可能会说：“我们要在接下来的 12 个月内损失一半的利润，”这并没有错，但更准确的说法是，“根据目前的预测，我们将在未来 12 个月内损失一半的利润，除非我们采取行动”，然后展示所使用的输入和假设。例如，建模者假设如下： 3) 运营的第一个月将售出 500 张门票。 3) 门票销售量将增加1.5第一个月后每月的百分比。 ) 路线之间没有蚕食。通常，在推出新产品时，一些现有客户会转向新产品。因为新路线服务于一个新区域，所以建模者预计不会发生任何自相残杀，也没有将其包含在此模型中。 ## 商科代写|商业建模代写Business Modeling代考|Structuring your model: What goes where 在设计模型的布局时，大多数有经验的建模师都遵循以下规则： 尽可能分开输入、计算和结果。清楚地标注模型的哪些部分包含输入、计算和结果。您可以将它们放在单独的工作表上或一个工作表上的不同位置，但要确保用户确切知道每个部分的用途。颜色编码有助于确保明确定义每个部分。 ) 将每一列用于相同的目的。这在构建涉及时间序列的模型时尤其重要。例如，在时间序列模型中，知道标签在 B 列，单位数据在 C 列，常数值在列D, 和列中的计算和, 使手动编辑公式时变得更加容易。 ) 每行或每列使用一个公式。这构成了最佳实践原则的基础，即使用绝对、相对和混合引用来保持公式的一致性，如第 4 章中更详细描述的那样。在数据块中保持公式一致，切勿在中途更改公式。 请参阅左侧和上方。模型应该像书一样在逻辑上阅读，这意味着应该从左到右，从上到下阅读。计算、输入和输出应按逻辑进行，以避免循环引用。请注意，有时从左到右或从上到下的数据流可能会与易用性和演示有些冲突，因此在设计布局时请使用常识。按照这个练习，你可以 避免在整个工作表上都有计算链接，这使得检查和更新变得更加困难。如果您以这种方式构建公式，Excel 的计算速度也会更快，因为它从左到右、从上到下进行计算，因此它不仅使您的模型更易于遵循，而且计算效率更高。 3) 使用多个工作表。避免将所有内容都放在一张纸上的诱惑。特别是当计算块相同时，对于必须重复的计算块使用单独的表格以避免需要在屏幕上滚动。 ) 包括文档表。明确列出假设和源数据的文档表是任何财务模型的关键部分。不应将封面与假设表混淆。一个模型永远不会有太多的文档！ ## 商科代写|商业建模代写Business Modeling代考|Defining inputs, calculations, and output blocks 通常，建模人员在构建模型时从后向前工作。输出或他们希望查看者或用户看到的部分在前面，计算在中间，源数据和假设在后面。就像执行摘要、董事会文件或其他报告一样，前几页应该包含普通观众需要一目了然的内容。如果他们需要更多信息，他们可以更深入地研究模型。 以下是关于模型中每个选项卡上可能包含的内容的一些指南：$封面：虽然不总是包括在内，但封面包含有关模型的许多详细信息。当然，除非您保持最新状态，否则封面并没有多大用处。如果您决定包含封面，您可以添加以下详细信息：

• 模型的更改和更新日志，包括日期、作者、更改详细信息及其对模型输出的影响，有助于进行版本控制
• 模型的目的以及未来的使用方式
• 谁最初编写了模型以及与谁联系以提出问题
• 目录
• 模型使用说明
• 关于模型限制、法律责任和警告的免责声明
• 使用模型不可或缺的全局或关键假设

## 有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

A financial model is usually built in order to answer a question or to solve a problem. For example, the question “Should I purchase this new asset?” can result in a model containing cash flow analysis, which compares the cash flow if the asset is purchased versus if it is not purchased. “How much should I pay for this new asset?” is an entirely different question, and the answer will be a single number or a range of possible numbers.
You need to identify the problem before beginning the model-building process.
For example, if the model you’re building is for the purpose of making a decision, you need to build at least two scenarios – one with the existing business and one including the new venture – as well as a comparison between them. Modelers sometimes call this a “do nothing” versus as “do something” scenario. So the model will consist of three components:
3) “Do nothing” scenario

) “Do something” scenario
Scenario comparison
In the example shown in Figure 3 -1, a small bus company has serviced two bus routes for many years. The financial model shows 12 months of historical data and has forecast the next 12 months. Due to a change in demographics and a new train line servicing the area, ticket sales for the northern route have been declining consistently, and the company expects this trend to continue. If the company does nothing, as shown, the profits will more than halve over a two-year period.

You can download a sample copy of this model in File $0302 . x l s x$ at www. dummies . com/go/financialmodelinginexcel fd2e.

You start building this model by creating the three tabs and determining that the comparison sheet should contain a comparison between the two scenarios. Then you design the “do nothing” scenario and then look at how different the numbers are if the company adds a new bus line.

Keeping models consistent is important. For this reason, the “do nothing” scenario contains an extra blank row in each block of data, which is where the new western route can be inserted. The Total Profit line is shown in row 27 of both scenario pages, which makes the model easier to follow, and less prone to error when linking the charts and summary page to the outputs.

## 商科代写|商业建模代写Business Modeling代考|Designing How the Problem’s

When you’ve identified the problem that needs to be solved, it’s very tempting to dive straight in and begin the model-building process, but it’s a good idea to stop for a moment to plan the model and determine how the output will look. When it comes to building a financial model, you want to start with the end in mind.

Start by creating a mockup design of the output page. You can do this in Excel, or by simply sketching it on a whiteboard or paper. It can be difficult to visualize what the output will look like until you have the data in it. Modelers aren’t often the most artistic types, but you should have at least some idea of the elements that need to be on the output page.

For example, for a business case, let’s say you want to show the net present value (NPV), internal rate of return (IRR), and payback period. To do this, you need cash flow, so the key elements will be revenue and expenses, from which you can derive profitability, and then the NPV, IRR, and payback. You can flesh out the outputs page something like the design shown in Figure $3-4$.

A financial model is only as good as its inputs or source data, and a large part of the modeler’s job is often collecting, interpreting, analyzing, and even manipulating or extrapolating the data to go into the model. In many cases, as much time can be spent collecting data as is spent actually building the model, so if you can collect the data in the correct format in the first place, this can save you a lot of time.

You often have to obtain data you need to build the model from other people or external sources, which can be a frustrating and time-consuming process. Here are some guidelines that can make the data-gathering process easier:
s) Let other parties know well in advance what information you need and its purpose.

) Give them a due date that is realistic for them and fits your time frame.
) Design the input sheets in your model so that the data can be pasted directly in.

## 商科代写|商业建模代写Business Modeling代考|Assumptions or input errors

Your model’s formulas may be calculating perfectly, but assumptions in financial models are a textbook case of “garbage in, garbage out.” If the assumptions you’ve used as inputs are incorrect, the model will also be incorrect.
When it comes to input errors there are two main types to consider:

) Data input: Data input errors can easily occur if you’re updating operating costs, for example, on a week-to-week basis. If these costs aren’t linked correctly or refreshed regularly, you can get an incomplete or inaccurate picture of the process. Sometimes linking this information to a separate, automatically generated file and using some of the new Modern Excel tools such as Get \& Transform (formerly called Power Query) can automate and expedite this process. Also, be sure to confirm who is responsible for updating the spreadsheet and make sure any changes to the process or update schedule don’t affect your model.
) User input: User input errors occur more frequently when you’re less familiar with the product or project you’re modeling. For example, when it comes to the salary costs of a program, you may factor in the benefits that an employee will receive and assume it will be 5 percent of their salary, which is a fairly standard across-the-board assumption. However, because you’re new to the organization, you may fail to take into account other factors that affect the employee’s benefits, such as an increase in the cost of delivering the dental and medical program that the company prides itself on. Suddenly, this drives the cost to $12.5$ percent of salary, completely blowing out all the staff costs you’ve so carefully calculated.
If you’re making assumptions, you need to record them, consider them, and lay them out carefully in your model. (See Chapter 4 for more information about assumptions documentation.) It’s also a good idea to confirm these inputs with the key stakeholders.

The old saying “Too many cooks spoil the broth” most certainly applies to building a financial model. Unless you have a strict, collaborative set of standards that will ensure that the model is laid out and assumptions are entered consistently, you’ll achieve the best result by having only one modeler working to build the model. When it comes to using the model, however, anyone should be able to use a wellbuilt model. If you’re worried about people messing up your calculations or entering inputs incorrectly, make sure your instructions and documentation explain how to use the model. Also, apply data validations or cell protection to the model to restrict changes the user can make.

## 商科代写|商业建模代写Business Modeling代考|Assumptions or input errors

) 数据输入：如果您要更新运营成本（例如，每周更新一次），则很容易出现数据输入错误。如果这些成本没有正确关联或没有定期更新，您可能会获得不完整或不准确的流程图片。有时将这些信息链接到一个单独的、自动生成的文件，并使用一些新的现代 Excel 工具，例如 Get \& Transform（以前称为 Power Query），可以自动化和加速这个过程。此外，请务必确认谁负责更新电子表格，并确保对流程或更新计划的任何更改不会影响您的模型。
) 用户输入：当您对正在建模的产品或项目不太熟悉时，用户输入错误会更频繁地发生。例如，当涉及到计划的工资成本时，您可能会考虑员工将获得的福利，并假设它将是他们工资的 5%，这是一个相当标准的全面假设。但是，由于您是该组织的新手，您可能无法考虑影响员工福利的其他因素，例如提供公司引以为豪的牙科和医疗计划的成本增加。突然间，这将成本推高到12.5百分之一的工资，把你精心计算的所有员工成本都花光了。

## 有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。