### 统计代写|多元统计分析代写Multivariate Statistical Analysis代考| Survival Data

statistics-lab™ 为您的留学生涯保驾护航 在代写多元统计分析Multivariate Statistical Analysis方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写多元统计分析Multivariate Statistical Analysis代写方面经验极为丰富，各种代写多元统计分析Multivariate Statistical Analysis相关的作业也就用不着说。

• 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

## 统计代写|多元统计分析代写Multivariate Statistical Analysis代考|Waiting Times

Survival Analysis is traditionally concerned with the waiting time to the occurrence of a particular event. This might be a terminal incident like death, as the name suggests, but more generally the event can be any well-defined circumstance. For example, the event can be some life-changing occurrence, such as cure from a disease, or winning the hand of the object of one’s desire, or finally convincing the editor that one’s paper should be accepted. Again, there is a whole parallel universe called reliability in which times to breakdown or repair of machines and systems is the subject of study. There are also numerous other applications including stimulus-response times, and performance times in sports and system operation. Response times, in particular, can have wide variation, for example, ranging from (a) a sprinter leaping into action after the starter’s gun to (b) a politician asked to apologise for wrecking the economy, education, employment, justice system, and so forth. The old saying, “You can wait till the cows come home” might apply to the latter.
The methods of Survival Analysis can be profitably applied to situations in which time is not time at all. For example, in studying construction materials it might be the breaking strength of a concrete block: one can think of the stress being increased steadily until the time of fracture. Again, it could be the level attained in some trial: imagine hanging in there as the test proceeds until you are forced to concede defeat. What such measurements do have in common is that they are positive, or at least non-negative, barring ingeniously contrived cases. Also, their values tend to have positively skewed distributions with long upper tails.

## 统计代写|多元统计分析代写Multivariate Statistical Analysis代考|Discrete Time

In most conventional applications of survival analysis the times are treated as being continuous, that is, measured on a continuous scale, and almost always as being positive or, at least, non-negative. This reflects a belief that time itself proceeds continuously, though not all physicists are convinced of this nowadays, apparently. Such philosophical puzzles need not detain us here-they just lead to sleepless nights. On the other hand, when one considers carefully the definition of failure time, there is plenty of room for consideration of discrete time.

Consider a system in continuous operation that is inspected periodically, manually or automatically. Suppose that, if one or more components are classified as effectively life-expired, the system is taken out of service for renewal or replacement. Then, discounting the possibility of breakdown between inspections, the lifetime of a component is the number of inspections to life expiration. Some systems have to respond to unpredictable demands, a typical task for standby units. A similar situation occurs when a continuously operating system is subject to shocks, peak stresses, loads, or demands. Such stresses can be regular, such as those caused by tides or weekly demand cycles, or irregular, as with storms and earthquakes. The lifetime for such a system is the number of shocks until failure.

## 统计代写|多元统计分析代写Multivariate Statistical Analysis代考|Censoring

In Survival Analysis it is almost obligatory to have to deal with censoring. The most common case is when the waiting time is right-censored. If this occurs at time $t$, it means that the actual time $T$ is only known to exceed $t$, that is, the extent of the information is that $T>t$. Such would arise, for example, with a machine still functioning at time $t$ when observation ceased at $5.30 \mathrm{p} . \mathrm{m}$. on Friday, or with an ex-offender still known to be on the right side of the law at time $t$ when probation monitoring finished. Another common example is with patients under observation after some treatment: they could be lost to follow-up if they moved away without leaving contact details and were consequently and subsequently lost sight of (“Mum, why do we always move at night?). Yet another situation is where a failure occurs for a reason different to the one under study. So, a patient might die of some condition other than the one being treated. In that case the analysis can be complicated by possible association between the different causes of failure-this is the subject of competing risks; see Part III.

Less common is left-censoring, when it is only known that failure occurred some time before observation was made. So, the game starts, then you need the loo, and when you return your mates are cheering because your team scored while you were indisposed. (Of course, you would probably have heard the roar of the crowd from your end of the stadium, but please overlook that slight flaw in the example. There is the legend of a supporter whose friends would plead with him to take a break; such was the observed association.) In medicine a left-censored time would result where the patient returns for

a scheduled check-up, which then indicates that the disease had recurred sometime previously. Formally, the information is just that $T<t$, where $t$ is observed.

Interval censoring means that the waiting time $T$ is not recorded precisely but can be bracketed, say between times $t_{1}$ and $t_{2}$. For example, the system might have crashed overnight, between leaving it running in the evening and returning to look at it the following morning. Again, the patient’s check-up at three months after treatment might show all clear, but then at six months indicate a recurrence of the disease sometime in between. Even recordings that are nominally exact might be just to the nearest minute or nearest day. It can be argued that virtually all survival times are interval censored, being rounded by the limited accuracy of the recording instrument. However, times are most often treated as exactly equal to the recorded value.

On the other hand, the starting time can also be subject to uncertainty. Switching on a machine is clear enough, but what about patients with chronic conditions? When someone is referred for medical treatment, and subsequently followed up, various initial times can be considered for the final analysis. Should it be when symptoms first appeared, relying on the memory of the patient? Should it be when the doctor was first consulted? Or when treatment started? Or when treatment finished? Such variations of definition can obviously have a significant effect on the analysis. It might be better to recognise that there is often a series of events, producing several inter-event times. Such multivariate data is the topic of Part II.

## 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。