## 统计代写|数据结构作业代写data structure代考|CS166

statistics-lab™ 为您的留学生涯保驾护航 在代写数据结构data structure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。我们的专家在代写数据结构data structure方面经验极为丰富，各种代写数据结构data structure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|数据结构作业代写data structure代考|Clusters and Flat Clustering

Clusters are groups of points that are similar to each other and dissimilar to points from other clusters. In terms of the underlying distribution, a cluster constitutes a connected area of high density around a mode of the distribution. Clusters may be determined automatically by clustering algorithms providing a flat clustering, or visually relying on the ability of human cognition to identify groups (see Gestalt laws of proximity and continuity detailed Sect. 1.3.2). Indeed, by looking at Fig. 1.7a, the reader gets an intuitive idea of what the clusters are for this dataset (a priori close to the automatic clustering of Fig. 1.8b).

Clustering algorithms identify a latent categorical variable indicating the cluster to which a given point belongs. Namely, they determine a mapping $\Omega: \mathcal{D} \longrightarrow \mathcal{L}$ assigning each data point $\xi_i$ to a category with a label $L_i=\Omega\left(\xi_i\right)$. The number of clusters, that is the number of possible values of that categorical variable, is a key parameter for a flat clustering. We may distinguish two main approaches for clustering of multidimensional data: the parametric approach used by partitioning algorithms and the density-based approach. For network data, the equivalent of clustering is community detection. In terms of graphs, communities (i.e. clusters) may be defined as groups of vertices linked together by many edges and linked to their surroundings by less edges [19].
Parametric Clustering
Partitioning algorithms, such as $k$-means [118] and $k$-medoids [96] split the space into $k$ convex regions parametrized by associated prototypes. Indeed, they assign each point of the datase to one of the clusters, so as to minimize the distances separating points from their clusters prototype. This prototype, which is respectively a centroid for $k$-means and a medoid for the $k$-medoids, provides a central tendency of the cluster. Formally, those algorithms seek the clustering that minimizes the cumulated Fréchet variance of all clusters, measured around their respective Fréchet means, which is the aforementioned prototype.

## 统计代写|数据结构作业代写data structure代考|Latent Variables Extraction and Manifold Learning

In the i.i.d hypothesis, the support of the theoretical probability distribution generating data points $\left{\xi_i\right}$ is considered as a manifold $\mathcal{M}$ immersed in the ambient data space $\mathcal{D}[9,81]$. The repartition of points along a manifold may be explained by the strong dependency between data space variables. In addition, one may assume that all these variables are local functions of a few independent latent variables with an additional noise [176], thus constituting a low-dimensional structure. That noise may induce small variations around the smooth structure of that manifold. Note that the manifold hypothesis may extend to datasets that are not generated by random processes. For instance, for the two open boxes and COIL-20 datasets (see Sect. 1.1.7), data lie on a low-dimensional manifold which is regularly sampled, and not randomly sampled.

Dimensionality Reduction (DR) in general aim at finding a mapping $\Phi: \mathcal{D} \longrightarrow$ $\mathcal{E}$, that associates each data point $\xi_i$ to a point $x_i=\Phi\left(\xi_i\right)$ in a low dimensional embedding space $\mathcal{E}$. A key parameter of dimensionality reduction is the embedding dimensionality $d$ (i.e. the dimensionality of $\mathcal{E}$ ). We distinguish here two sub-cases of $\mathrm{DK}$ : manifold learning and spatialization. The ideal goal of manifold learning is to extract latent variables parametrizing the manifold, which explain the variability of data. Those hypothetical variables may also be referred to as curvilinear components of the manifold [54]. In that case, the embedding dimensionality defines the number of variables to extract. A possible value for that parameter is the intrinsic dimensionality, which corresponds locally to the number of curvilinear components require to parametrize the manifold (see Sect. 2.2). Manifold learning may be used as a pre-processing step for other machine learning applications (e.g., classification or clustering), in order to mitigate the curse of dimensionality [155], to compress the data [179], or to filter out the noise [176]. Inversely, spatialization aims at providing a visual representation of high-dimensional data (see Sect. 1.3.2). As a result, the embedding dimensionality is constrained by the perceptual capabilities of the data analyst, limiting the number of dimensions to at most three for visualization with only one scatter plot. Satisfying this strong constraint on dimensionality often requires distortions of the underlying data structure. Note that the equivalent of DR for network data is graph embedding (also called graph layout).

## 广义线性模型代考

statistics-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。

## 统计代写|数据结构作业代写data structure代考|COS241

statistics-lab™ 为您的留学生涯保驾护航 在代写数据结构data structure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。我们的专家在代写数据结构data structure方面经验极为丰富，各种代写数据结构data structure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|数据结构作业代写data structure代考|Multidimensional Data

Multidimensional data (also called feature data or tabular data) correspond to a set of $N$ data points (or feature vectors) $\xi_i$ in a high dimensional vector space $\mathcal{D}$. This data space (or feature space) $\mathcal{D}$ of dimensionality $\delta$ often corresponds to $\mathbb{R}^\delta$. A multidimensional dataset may be stored in a data matrix $\Xi$ of size $N \times \delta$. The element $(i, k)$ of that matrix, denoted $\xi_{i k}$, contains the value of the $k$ th variable for the $i$ th data point $\xi_i$.

Multidimensional data is thus the natural format for treating data tables, which are the basic element of relational databases (e.g., SQL databases). Indeed, those tables are organized by rows and columns, each row corresponding to an instance, and each column being associated with an attribute (or feature) of that instance. In statistics, those instances are also called individuals or observations.

The features are either quantitative, such as numerical or ordinal variables, or qualitative, as for categorical or boolean variables. Yet, all these types of variables may be stored in a common numerical matrix with, for example, ordinal variables represented by successive integers, boolean variables by 0 and 1 values and categorical variables represented by several boolean variables (one by category), each indicating whether the observation belongs to that category [179].

For a data matrix $\boldsymbol{\Xi}$, an associated distance matrix $\boldsymbol{\Delta} \boldsymbol{\Xi}$ may be obtained by choosing a specific metric $\Delta$ on the data space. Dimensionality reduction seeks to convert metric data into multidimensional data in a low dimensional space, thus leading to a set of $N$ embedded points $x_i$ in a low dimensional embedding space $\mathcal{E}$ of dimensionality $d$.

## 统计代写|数据结构作业代写data structure代考|Network Data

Networks data characterize relations between instances, as can be stored in a relation table in relational databases. As such, they can be modelled by a graph (as formally defined by Definition 1.4). They may either be hierarchical data (tree structures) or relational data (graph structures).

Definition 1.4 A weighted directed graph (or digraph) $G=(V, E, W)$ is composed of:

• $V$ the set of $N$ vertices,
• $E \subseteq V \times V$ the set of directed edges with cardinal $|E| \leqslant N^2$,
• $W$ the set of weights associated to the edges.
The vertices $i \in V$ of that graph correspond to instances and edges $(i, j) \in E$ to the relations existing between the instances $i$ and $j$. The associated weights $w_{i j}$ characterize those relations. They may, for example, be measures of similarity $\gamma_{i j}$ or measures of dissimilarity $\Delta_{i j}$. A graph weighted by similarities may be represented by its adjacency matrix whose element $(i, j)$ contains the weight $w_{i j}$ if the edge $(i, j)$ exists and 0 otherwise. For non-complete graph, that matrix is sparse. This representation could be adapted to graphs weighted by dissimilarities by denoting non-existing edges with elements equal to $+\infty$.
Graph Distances
Weights of a graph often define similarities or dissimilarities between some pairs of vertices. Graph distances rely on this sparse information to define a full distance matrix $\Delta$ measuring dissimilarity between all pairs of vertices.

Shortest path distances [175] find the path of minimum length between two vertices in the graph weighted by dissimilarities. Conversely, in graphs weighted by similarities, distances tend to rely on random walks. Those random walks take a random path resulting from successive random transitions, where the probability of transitioning from a vertex $i$ to any other vertex $j$ is proportional to the weight $w_{i j}$.

## 统计代写|数据结构作业代写data structure代考|Network Data

• $V$ 的集合 $N$ 顶点，
• $E \subseteq V \times V$ 有基数的有向边集 $|E| \leqslant N^2$,
• $W$ 与边关联的一组权重。
顶点 $i \in V$ 该图对应于实例和边缘 $(i, j) \in E$ 实例之间存在的关系 $i$ 和 $j$. 相关权重 $w_{i j}$ 表征 这些关系。例如，它们可能是相似性的度量 $\gamma_{i j}$ 或不同的措施 $\Delta_{i j}$. 由相似性加权的图可以 由其元素的邻接矩阵表示 $(i, j)$ 包含重量 $w_{i j}$ 如果边缘 $(i, j)$ 存在，否则为 0 。对于非完全 图，该矩阵是稀疏的。这种表示可以通过用等于 $+\infty$.
图形距离图形
的权重通常定义某些顶点对之间的相似性或不同性。图距离依赖于这种稀疏信息来定义一 个完整的距离矩阵 $\Delta$ 测量所有顶点对之间的差异性。
最短路径距离 [175] 找到图中两个顶点之间由差异加权的最小长度路径。相反，在由相似性加 权的图中，距离往往依赖于随机游走。这些随机斿走采用由连续随机转换产生的随机路径，其 中从顶点转换的概率 $i$ 到任何其他顶点 $j$ 与重量成正比 $w_{i j}$.

## 广义线性模型代考

statistics-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。

## 统计代写|数据结构作业代写data structure代考|RU101

statistics-lab™ 为您的留学生涯保驾护航 在代写数据结构data structure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。我们的专家在代写数据结构data structure方面经验极为丰富，各种代写数据结构data structure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|数据结构作业代写data structure代考|Measuring Dissimilarities and Similarities

Data instances of any type may be considered as points in a metric space as long as one may define a metric or distance function to measure the dissimilarity between two instances. This metric space $(\mathcal{D}, \Delta)$ is a topological space equipped with a distance $\Delta$, which provides for each pair of elements of that space a numerical score of their dissimilarity. This proper notion of distance is defined by:

Definition 1.1 A function $\Delta: \mathcal{D} \times \mathcal{D} \rightarrow \mathbb{R}^{+}$is a distance (or metric) over the space $\mathcal{D}$ if and only if it satisfies the following conditions for all $\xi_i, \xi_j, \xi_k \in \mathcal{D}$ :

• $\Delta\left(\xi_i, \xi_j\right) \geqslant 0$ (non-negativity),
• $\Delta\left(\xi_i, \xi_j\right)=0$ iff $\xi_i=\xi_j$ (identity of indiscernibles),
• $\Delta\left(\xi_i, \xi_j\right)=\Delta\left(\xi_j, \xi_i\right)$ (symmetry)
• $\Delta\left(\xi_l, \xi_j\right) \leqslant \Delta\left(\xi_l, \xi_k\right)+\Delta\left(\xi_k, \xi_j\right)$ (triangle inequality or sub-additivity).
Those distances extend to abstract spaces the spatial notion of distance in our three-dimensional physical space, measured using the Euclidean distance (see Sect. 1.1.4). As a tool for measuring dissimilarities, one may also consider pseudometrics which do not satisfy all properties of the Definition 1.1. When not otherwise stated dissimilarities between data are computed with the Euclidean distance.

Metric spaces are a more general case of normed vector spaces, that is spaces equipped with a norm $|\cdot|$ measuring the size of a vector, defined as follows:

Definition 1.2 A function $|\cdot|: \mathcal{D} \longrightarrow \mathbb{R}^{+}$is a norm if and only if it satisfies the properties for all $\xi_i, \xi_j \in \mathcal{D}$ and $\alpha \in \mathbb{R}$ :

• $\left|\alpha \xi_i\right|=|\alpha|\left|\xi_i\right|$ (homogeneity),
• $\left|\xi_i\right|=0 \Rightarrow \xi_i=0$ (separation),
• $\left|\xi_i+\xi_j\right| \leqslant\left|\xi_i\right|+\left|\xi_j\right|$ (triangle inequality).
In a normed vector space, a distance is naturally defined between all pairs of point by computing the norm of their difference:
$$\Delta\left(\xi_i, \xi_j\right)=\left|\xi_i-\xi_j\right| .$$
Normed vector spaces include the subcase of inner product spaces (equipped with an inner product $\langle\cdot, \cdot\rangle$. An inner product must satisfy the following definition.

## 统计代写|数据结构作业代写data structure代考|Neighbourhood Ranks

Neighbourhood ranks reduce the information of distances for a given dataset to an ordering, considering independently each row of the distance matrix. The rank $\rho_{i j}$ describes the position of point $\xi_j$ in the neighbourhood of point $\xi_i$, that is its place in the sorting of data points by their distance to point $\xi_i$. Replacing distances values by their ranks ensures more robustness to the phenomenon of norm concentration detailed in Sect. 2.1. Formally, a rank $\rho_{i j}$ indicates that point $\xi_j$ is the $\rho_{i j}$ th nearest neighbour of point $\xi_i$. By convention, we set $\rho_{i i} \triangleq 0$.

For each data point $\xi_i$, we define the neighbourhood permutation $\tilde{v}i: \llbracket 0, N-1 \rrbracket \longrightarrow \llbracket 1 ; N \rrbracket$ as the mapping returning for a given rank $\kappa$, the index $j$ of the $\kappa$ th nearest neighbour of $\xi_i$ in that space. Namely, $\tilde{v}_i(\kappa)$ is the index so that $\xi{\tilde{v}i(\kappa)}$ is the $\kappa$ th nearest neighbour of $\xi_i$. We may note that $\tilde{v}_i\left(\rho{i j}\right)=j$ and that, using the bijectivity of the permutation, $\rho_{i j}=\tilde{v}_i^{-1}(j)$ (which may be an alternative definition of ranks).

We also define $\kappa$-neighbourhoods $v_i(\kappa)$ as the set of indices of the $\kappa$ nearest neighbours of $i$. This may be formally defined based on ranks as $v_i(\kappa)={j \neq i \mid$ $\left.\rho_{i j} \leqslant \kappa\right}$, or as the image by the neighbourhood permutation $\tilde{v}_i$ of the set $\llbracket 1 ; \kappa \rrbracket$, namely $v_i(\kappa)=\tilde{v}_i(\llbracket 1 ; \kappa \rrbracket)$. The link between distances, neighbourhood ranks and neighbourhood permutations is illustrated Fig. 1.1, for an abstract metric dataset.

## 统计代写|数据结构作业代写data structure代考|Measuring Dissimilarities and Similarities

• $\Delta\left(\xi_i, \xi_j\right) \geqslant 0$ (非负性)，
• $\Delta\left(\xi_i, \xi_j\right)=0$ 当且仅当 $\xi_i=\xi_j$ (不可辨认者的身份），
• $\Delta\left(\xi_i, \xi_j\right)=\Delta\left(\xi_j, \xi_i\right)$ (对称)
• $\Delta\left(\xi_l, \xi_j\right) \leqslant \Delta\left(\xi_l, \xi_k\right)+\Delta\left(\xi_k, \xi_j\right)$ (三角不等式或子可加性) 。
这些距离将我们的三维物理空间中距离的空间概念扩展到抽象空间，使用欧几里德距离测 量 (参见第 1.1.4 节) 。作为一种测量差异的工具，人们还可以考虑不满足定义 $1.1$ 的所 有属性的伪度量。如果没有另外说明，数据之间的差异是用欧氏距离计算的。
度量空间是赋范向量空间的更一般情况，即配备范数的空间 |·|测量向量的大小，定义如下:
定义 $1.2$ 函数 $|\cdot|: \mathcal{D} \longrightarrow \mathbb{R}^{+}$是一个规范当且仅当它满足所有的属性 $\xi_i, \xi_j \in \mathcal{D}$ 和 $\alpha \in \mathbb{R}$ :
• $\left|\alpha \xi_i\right|=|\alpha|\left|\xi_i\right|$ (同质性)，
• $\left|\xi_i\right|=0 \Rightarrow \xi_i=0$ (分离) ，
• $\left|\xi_i+\xi_j\right| \leqslant\left|\xi_i\right|+\left|\xi_j\right|$ (三角不等式) 。 在陚范向量空间中，通过计算点对差的范数自然地定义了所有点对之间的距离:
$$\Delta\left(\xi_i, \xi_j\right)=\left|\xi_i-\xi_j\right| .$$
赋范向量空间包括内积空间的子情况 (配备内积 $\langle\cdot, \cdot\rangle$. 内积必须满足以下定义。

## 统计代写|数据结构作业代写data structure代考|Neighbourhood Ranks

$\tilde{v} i: \backslash$ llbracket $0, N-1 \backslash$ rrbracket $\longrightarrow \backslash$ llbracket $1 ; N \backslash$ rrbracket作为给定等级的 $\kappa$ 的第 th 个最近邻 $\xi_i$. 我们可能注意到 $\tilde{v}i(\rho i j)=j$ 并且，使用排列的双射性， $\rho{i j}=\tilde{v}i^{-1}(j)$ (这可能是等级的另一种定义) 。 我们还定义 $\kappa$-社区 $v_i(\kappa)$ 作为指数的集合 $\kappa$ 最近的邻居 $i$. 这可以根据等级正式定义为 V_i(lkappa)={j Ineq i mid\$\$Vleft.Irho{i j} leqslant Ikappalright}}，或者作为邻域非列的图像 $\tilde{v}_i$ 集 合的 $\backslash$ llbracket $1 ; \kappa \backslash$ rrbracket, 即 $v_i(\kappa)=\tilde{v}_i(\backslash$ llbracket $1 ; \kappa \backslash$ rrbracket). 对于抽象度 量数据集，距离、邻域等级和邻域排列之间的联系如图 $1.1$ 所示。

## 广义线性模型代考

statistics-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。

## 统计代写|数据结构作业代写data structure代考|Trees

statistics-lab™ 为您的留学生涯保驾护航 在代写数据结构data structure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。我们的专家在代写数据结构data structure方面经验极为丰富，各种代写数据结构data structure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|数据结构作业代写data structure代考|What is a Tree

A tree is a data structure similar to a linked list but instead of each node pointing simply to the next node in a lincar fakhion, each node points to a number of nodes. Tree is an example of non-linear data structures $A$ tree structure is a way of representing the hierarchical nature of a strocture in a graphical form.

In trees ADT (Abstract Data Type), the order of the elenents is not important. If we need ordering information linear data structures like linked lists, stacks, queues, cte, cin be used.

## 统计代写|数据结构作业代写data structure代考|Binary Tree Traversals

In order to process trees, we necd a mechanism for traversing them, and that forms the subject of this section. The process of visiting all nodes of a tree is called tree traversal. Fach node is processed only once but it may be visited more than once. As we have already secn in linear data structures (like linked lists, stacks, queues, cte.), the clemeats are visated in sequential order. But, in trec structures there are nuany differeat ways.
Tree traversal is lake searching the tree, excepx that in traversal the goal is to move through the tree in a particular order. In addition, all nodes are processed in the traversal but sear ching stops when the required aode is foumd.

In preorder traversal, each node is processed before (pre) either of its subtrees. Thais is the simplest traversal to uaderstand. However, cven though each node is processed before the subtrees, it still requires that some information must be maintaincd while moving down the tree. In the example abowe, 1 is processed first, then the left subtree, and this is followed by the right subtree.

Therefore, processing nust return to the right subtree after fanishiug the processing of the left subtree. To nuove to the right subtree after processing the left subtrec, we must maintain the root information. The obvious ADT for such information is a stack. Because of its IFO structure, it is possible to get the information about the right subtrees back in the reverse order.
Preorder traversal is defined as follows:

• Visal the root.
• Traverse the left subtree un Prcordcr.
• Traverse the right subtree in Preorder.

## 统计代写|数据结构作业代写data structure代考|Minimum depth of a binary tree

Minimum depth of a binary tree: Given a binary tree, find its mimimum depth. The minimum depth of a binazy tree is the number of nodes along the shortest path from the root node down to the nearest leaf node. For example, naimun depth of the following binary tree is $\supsetneqq$.

Solution: The algorithm is similar to the algorithmo of finding depth (or height) of a binary trec, except here we are finding minimum depth. One simplest approach to solve this problem would be by usimg recursion. But the question is when do we stop it? We stop the recursave calls when it is a leaf rode or None.
Algorithm I ret root be the pointer to the root aode of a subtrec.

• If the root is equal to None, then the maimimum depeh of the bänary tree would be $0 .$
• If the root is a keaf node, then the minimum depth of the binary trec woudd be 1 .
• If the root is not a leaf node and if left subtree of the root is None, then find the maimimum depth in the right suberce. Otherwise, find the naimimum depth in the left subtree.
• If the root is not a leaf node and both left suberee and right subtree of the root are aot None, then recursively find the mainimum depth of left and right subtree. I ct at be leftSubtreeMinDepth and rightSubtreeMinDepth respectively.
• To get the maininum height of the binary ree rooted at root, we will take nuininaum of leftSubtreeMinDepth and rightSwhtreeMinDepth and 1 for the ront node.

## 统计代写|数据结构作业代写data structure代考|Binary Tree Traversals

• 维萨根。
• 遍历左子树 un Prcordcr。
• 在 Preorder 中遍历右子树。

## 统计代写|数据结构作业代写data structure代考|Minimum depth of a binary tree

• 如果根等于无，则二叉树的最大深度为0.
• 如果根是 keaf 节点，则二进制 trec 的最小深度将是 1 。
• 如果根不是叶子节点并且根的左子树是None，则在右子节点中找到最大深度。否则，在左子树中找到最大深度。
• 如果根不是叶子节点，并且根的左子树和右子树都不是None，则递归找到左子树和右子树的最大深度。我分别在 leftSubtreeMinDepth 和 rightSubtreeMinDepth 处。
• 为了得到以根为根的二叉树的主高度，我们将 leftSubtreeMinDepth 和 rightSwhtreeMinDepth 的 nuininaum 和 1 用于 ront 节点。

## 广义线性模型代考

statistics-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。

## 统计代写|数据结构作业代写data structure代考|Queues

statistics-lab™ 为您的留学生涯保驾护航 在代写数据结构data structure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。我们的专家在代写数据结构data structure方面经验极为丰富，各种代写数据结构data structure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|数据结构作业代写data structure代考|What is a Queue

A queue is a data structure used for storing data (simalar to I inked lists and Stacks). In queuc, the order in which data arrives is important. In general, a queue is a liac of people or things waiting to be served in sequential order starting at the beginaing of the line or sequence.

Definition: A queue is an ordered list in which insertions are done at one cnd (rear) and deletions are done at other end (front). The first element to be inserted is the first one to be deleted. Hence, it is called First in First out (FIFO) or Last in I.ast out (LII.O) list.

Sinalar to Stacks, special namacs are given to the two chaages that can be maade to a queuc. When an clearcnt is iaserted in a queuc, the concept is called EnQueue, and when an clensent is removed from the queue, the concept is called DeQueue.

DeQueueing an empty queue is called underflow and EnQueuing an element in a full queue is called over flow. Generally, we treat them as exceptions. As an exanuple, consuder the snapshot of the quete.

## 统计代写|数据结构作业代写data structure代考|How are Queues Used

The concept of a queuc can be explained by observing a line at a reservation counter. When we enter the lias, we stand at the end of the line and the person who is at the front of the line is the one who will be served next. He will exit the queue and be served.
As this happens, the nexi person wall come at the head of the line, wall exit the queue and will be served. As cach person at the head of the line kecps cxiting the queue, we nocve towards the head of the line. Finally, we wall reach the head of the line and we will exalt the queue aad be served. This behavion is very useful in casc3 where there is a necd to haintain the order of arrival.

## 统计代写|数据结构作业代写data structure代考|Queues

As you can see, the producer and consumer do not necessarily alternate in execution. In this solution, we use the Quete. We use random_randint0 to nake production and consumption sonewhat varied.

The writeQ0 and readQ0 functions each have a specific purpose: to place an object in the queuc-ue are using the string ‘MONK’, for example-ind to consume a quetued object, respectively. Notice that we are producing one object and reading one object each tine.

The producer0 is going to nun as a single thread whose sole purpose is to produce an item for the queuc, wait for a bit, and then do it again, up to the specified number of times, chosen randomly per script execution. The consumer() will do likewise, with the exception of consuming an item, of course.

You will notice that the random number of seconds that the producer slecps is in general shorter than the amount of time the consumer sleeps. This is to discourage the consumer from trying to take itens from an empty queue. By giving the producer a shorter time period of waiting, it is more likely that there will already be an objeet for the consumer to consume by the time their tum rolk around again.
These are just setup lines to set the total number of threads that are to be spawned and executed.
$\mathrm{~ F u a d l y , ~ w e ~ h a v e ~ u m ~ a n a i n 0 ~ f u n c u i o n , ~ w h i c h ~ s h r u b l e l ~ l e o k ~ y u i t e ~ s a i}$ appropriate threads and send them on their way, finishing up when both threads have conchded execution.

We infer from this example that a program that has multiple tasks to perform can be organized to use separate threads for each of the tasks. This can result in a much cleaner program design than a single-threaded program that attempts to do all of the tasks.

We illustrated how a single-threaded process can limit an application’s performance. In particular, programs with independent, nondeterministic, and non-causal tasks that execute sequentially can be improved by division into separate tasks executed by individual threads. Not all applications will bencfit from multithreading due to overhead and the fact that the Python interpreter is a single-threaded application, but now you are nore cognizant of Python’s threading capabilities and can use this tool to your advantage when appropriate.

## 统计代写|数据结构作业代写data structure代考|What is a Queue

Sinalar 到 Stacks，特殊的 namacs 被赋予了两个可以编入队列的 chaages。当一个 clearcnt 在队列中被插入时，这个概念被称为 EnQueue，当一个 clensent 从队列中被移除时，这个概念被称为 DeQueue。

## 统计代写|数据结构作业代写data structure代考|Queues

writeQ0 和 readQ0 函数各有一个特定目的：将对象放入队列中 – 使用字符串“MONK”，例如 -ind 分别使用队列中的对象。请注意，我们正在生成一个对象，并且每个齿读取一个对象。

producer0 将作为单个线程运行，其唯一目的是为队列生成一个项目，稍等片刻，然后再做一次，直到指定的次数，每次脚本执行随机选择。consumer() 也会做同样的事情，当然，除了消费一个项目。

F在一种dl是, 在和 H一种在和 在米 一种n一种一世n0 F在nC在一世这n, 在H一世CH sHr在bl和l l和这ķ 是在一世吨和 s一种一世适当的线程并在途中发送它们，当两个线程都已确定执行时完成。

## 广义线性模型代考

statistics-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。

## 统计代写|数据结构作业代写data structure代考|Stacks

statistics-lab™ 为您的留学生涯保驾护航 在代写数据结构data structure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。我们的专家在代写数据结构data structure方面经验极为丰富，各种代写数据结构data structure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|数据结构作业代写data structure代考|What is a Stack

A stack is a simple data structure used for storing data (simailar to Lanked Lists). In a stack, the order in which the data arrives is important. A pile of plates in a cafeteria is a good example of a stack. The plates are added to the stack as they are cleaned and they are placed on the top. When a plate, is required it is taken from the top of the stack. The first plate placed on the stack is the last one to be used.

Definition: A stack is an ordered list in which insertion and deletion are done at one end, called top. The last clement inserted is the first one to be delcted. Hence, it is called the Last in First out (I.IFO) or Furst in Last out (FILO) list.

Special names are given to the two changes that can be made to a stack. When an clenuent is inserted in a stack, the concept is called push, and when an element is removed from the stack, the concept is called pop. Tryang to pop out an cmpty stack is called under flow and trying to push an elenueat in a full stack is called overflow. Geacrally, we treat then as exceptions. As an example, consider the snapshots of the stack.

## 统计代写|数据结构作业代写data structure代考|How Stacks are Used

Consider a working day in the office. Let us assume a developer is working on a long-term project. The manager then gives the developer a uew task which is maore important. The developer pusts the long term project aside and begins work on the asew tasla. The phone rings, and this is the highest pronory as it must be answered immediately. The developer pushes the present task into the peadiag tray and answers the phone.

When the call is complete the task that was abandoned to answer the phone is retrieved from the pendirg tray and work progresses. To take another call, it nay have to be handled in the sanve manner, but eventually the new task will be funished, and the developer can draw the loangtern project from the pending tray and continue with thaat.

## 统计代写|数据结构作业代写data structure代考|Dynamic Array Implementation

First, ket’s consider how we inplemented a simple array-based stack. We took one index variable top which points to the iadex of the most. recenthy inserted clement in the stack. To insert (or push) an element, we increment top index and then place the new element at that index.
Simalarly, to delete (or pop) an element we take the element at top index and then decrenent the top index. We represent an empty quete with top value equal to $-1$. The issue that still needs to be resolved is what we do when all the slots in the fixed size array stack are oceupicdi? First tryy What if we increment the size of the aray by 1 every time the stack is fulle?

• Pusha 0 ibcrease size of $\mathrm{S} |$ by 1
• Pop0: decrease size of Sll by 1
Issues with this approach?
This way of incrementing the array size is too expensive. Let us see the reason for this. For example, at $n=1$, to push an element create a new array of size 2 and copy all the old array elements to the new array, and at the end add the new element. At $n=2$, to push an element create a new array of size 3 and copy all the old array elements to the new array, and at the end add the new elenent.

Similarly, at $n=n-1$, if we want to push an element create a new array of size $n$ and copy all the old array elements to the new array and at the end add the new element. After $n$ push operations the total tine $T(n)$ (number of copy operations) is proportional to $1+2+\ldots+$ $n \approx \mathrm{O}\left(n^{2}\right)$.
Alternative Approach: Repeated Doubling
Let us improve the conplexity by using the array doubling technique. If the array is full, create a new array of twice the size, and copy the itens. With this approash, pushing $n$ items take time proporional to $n$ (not $n^{2}$ ).
For simplieity, let us aosune that initinlly we started waith $n=1$ and moved up to $n=32$. That means, we do the doubling at $1,2,4,8,16$. The other way of analyzing the same approach is: at $n=1$, if we want to add (push) an element, double the current size of the array and copy all the elements of the old array to the new array.

## 统计代写|数据结构作业代写data structure代考|Dynamic Array Implementation

• Pusha 0 ibcrease 大小小号|1
• Pop0：将 Sll 的大小减小 1
这种方法有问题吗？
这种增加数组大小的方法太昂贵了。让我们看看这其中的原因。例如，在n=1，要推送一个元素，创建一个大小为 2 的新数组，并将所有旧数组元素复制到新数组，最后添加新元素。在n=2，要推送一个元素，创建一个大小为 3 的新数组并将所有旧数组元素复制到新数组，最后添加新元素。

## 广义线性模型代考

statistics-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。

statistics-lab™ 为您的留学生涯保驾护航 在代写数据结构data structure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。我们的专家在代写数据结构data structure方面经验极为丰富，各种代写数据结构data structure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

By the time we traverse the complete list (for creating the hash table), we can find the list length. I ct us say the list length is $M$. To find $n^{\text {th }}$ from the end of linked list, we can convent this to $(M-n+1)^{\text {th }}$ from the beginuing. Sance we already know the length of the list, it is just a matter of retuming $(M-n+1)^{\text {th }}$ key value from the hash table.
‘ Iine Complexity: I inve lor creating the hash table, $T(m)=()(m)$. Space Cionaplexity: Since we need to create a hash table of size $m$, O( $m)$.
Problem-4 Can we use Problem-3 approach for solving Problem-2 without creating the hash table?
Solution Yeg. If we observe the Problenh3 solution, what we are actually doing is finding the size of the linked list. That means we are using the hash table to find the size of the linked list. We can find the length of the linked list just by starting at the head node and traversing the list. So, we can find the length of the list without creating the hash table. After finding the length, compute $M-n+1$ and with one more scan we can get the $(M-n+1)^{\text {th }}$ node from the beginning. This solution needs two scans: one for finding the length of the list and the other for finding $(M-n+1)^{t h}$ node from the hegianing-
Time Complexity: Time for finding the length + Time for finding the $(M-n+1)^{\text {th }}$ node from the beginning. Therefore, $T(n=O(n)+$ $O(n) \approx O(n)$. Space Complexity: $O(1)$. Hence, no need to create the hash table.
Problem5 Can we solve Problen-2 in one scan?
Solution: Yes. Efficient Approach: Use two pointers $p N$ thNode and $p$ Temp. Initially, both point to head node of the list. $p N$ thNode starts moving only alter $p$ Temp has made $n$ mones. From there both mowe forward until $p$ Temp reaches the end of the list. As a result, $p N$ thNode points to $n^{\text {th }}$ node from the end of the linked list.
Notet At any poant of time both move one node at a time.

## 统计代写|数据结构作业代写data structure代考|Efficient Approach

Solution: Yes. Fincient Approed QMemoryleas Appronch): The space conplexity can be reduced to O(1) by considering two pointers at differeat speed – a slow pointer and a fast pointer. The slow poanter moves one step at a time while the fast pointer mowes two steps at a tine. This problem was solved by Floyd. The solution is named the Floyd cycle finding algorithm. It uses two pointers moving at different speeds to walk the linked list. If there is no cycle in the list, the fast poanter will eventually reach the ead and we can return false in this case. Now consider a cyclic list and imagiae the slow and fast pointers are two rumers racing around a circle track. Once they enter the loop they are expected to neet, which denotes that there is a loop.

This works becanse the only way a faster movang pointer would point to the sanae location as a slower moving pointer is if sonachow the entire list or a part of it is circular. Think of a tortoise and a hare rumaing on a track. The faster numang hare will catch up with the tortoise if they are ruming in a loop. As an exanple, consider the followanng exmple and trace out the Floyd algonthm. From the diagrans below we can see that after the final step they are meeting at sone point in the loop which nay not be the starting point of the loop.
Note: slowPtr (tortoise) moves one pointer at a tine and fastPtr (hare) mones two pointers at a tine.

## 统计代写|数据结构作业代写data structure代考|Algorithm

Create two stacks one for the first list and one for the second list.
Traverse the first list and push all the node addresses onto the first stack.
Traverse the second list and push all the node addresses onto the second stack.
Now both stacks contain the node address of the corresponding lists.
Now compare the top node address of both stacks.
If they are the same, take the top elements from both the slacks and keep them in some temporary variable (since both node addresses are node, it is enough if we use one temporary varable).
Continue this process until the top node addresses of the stacks are not the same.
This point is the one where the lists merge into a single list.
Return the value of the tenporary variable.

## 数据结构代写

‘ 线复杂性：我想创建哈希表，吨(米)=()(米). Space Cionaplexity：因为我们需要创建一个大小为米， 这（米).

## 广义线性模型代考

statistics-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。

## 统计代写|数据结构作业代写data structure代考|What is a Linked List

statistics-lab™ 为您的留学生涯保驾护航 在代写数据结构data structure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。我们的专家在代写数据结构data structure方面经验极为丰富，各种代写数据结构data structure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|数据结构作业代写data structure代考|Issues with Linked Lists

There are a number of issues wàth linked lists. The main disadvautage of lanked lists is access time to individual elements. Array is randonaccess, which means it takes $\mathrm{O}(1)$ to access any clement in the array. I inked lists ake $O(n)$ for access to an element an the list in the worst case. Another advantage of arrays in access tine is spacial locality in menory. Arays are defined as contiguous blocks of nuenory, and so any array element will be physically near its neighbors. This greatly benefits from modern CTI caching methods.

Although the dynamic allocation of storage is a great advantage, the overhead with storing and retricving data can nake a big differeace. Sometimes limked lists are hard to manipulate. If the last item is deleted, the last but one must then have its pointer changed to hold a None reference. This requires that the list is traversed to find the last but one link, and its poanter set to a None relerence. Finally, linked lists waste menory in terms of extra reference points.

The advantage of a doubly linked list (also called two – way linked list) is that given a node in the list, we can navigate in both directions. A mode in a singly linked list cuamot be renoysd uakss we have the poiater to its predecessor. But in a doubly linked list, we can delete a mode even if we dou’t have the previous mode’s address (since each node has a left pointer pointiag to the previous node and can move backward).

• Each node requires an extra pointer, requiring more space.
• The insertion or deletion of a node takes a bit longer (more pointer operations).
Similar to a singly linked list, let us implement the operations of a doubly linked list. If you understand the singly linked list operations, then doubly linked list operations are obwious. Following is a type declaration for a doubly linked list of integers:

## 统计代写|数据结构作业代写data structure代考|Skip Lists

Binary trees can be used for represcuting abstract data types such as dictionaries and ordered lists. They work well when the elenucnts are inserted in a randon order. Sonve sequences of operations, such as inserting the elensents in order, produce degcnerate data stroctures that give very poor performance. If it were possable to randomaly permute the list of itens to be inserted, trees would work well waith high probability for any iaput sequence. In most cases queries must be answered oas-line, so randomly permutimg the anput is impractical. Balanced tree algorithas re-arrange the tree as operations are performed to maintain certain balance couditions and assure good performance.

Skip list is a data structure that can be used as an altemative to balanced biaary trees (refer to Trees chapter). As compared to a binary trec, skip lists allow quick search, insertion aad deletion of elements. This is achicved by using probabilistic balaucing rather than strictly enforce balancing. It is basically a linked list with additional poanters such that internediate modes can be skipped. It uses a randon mumber generator to maike some decisions.In an ordinary sorted linked list, search, insert, ausd delete are in $\mathrm{O}(\mathrm{n})$ because the list must be scanned node-by-node from the head to find the relevant node. If somehow, we could scan down the list in bagher steps (skip down, as it were), we would reduce the cost of scauniag. This is the fuadanacntal xlea behind Skip I.sts.

## 统计代写|数据结构作业代写data structure代考|Issues with Linked Lists

• 每个节点都需要一个额外的指针，需要更多空间。
• 节点的插入或删除需要更长的时间（更多的指针操作）。
类似于单链表，让我们实现双链表的操作。如果您了解单链表操作，那么双链表操作是显而易见的。以下是整数双向链表的类型声明：

## 广义线性模型代考

statistics-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。

## 统计代写|数据结构作业代写data structure代考|Backtracking

statistics-lab™ 为您的留学生涯保驾护航 在代写数据结构data structure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。我们的专家在代写数据结构data structure方面经验极为丰富，各种代写数据结构data structure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|数据结构作业代写data structure代考|Solutions

Solution:
def appendAt Frout $(\mathrm{x}, 1 \mathrm{j})$
return $\mid \mathrm{x}+$ clemeat for clement in L]
chef bitStrings(n):
if $\mathrm{n}=0$ – retura $[1$
if $\mathrm{a}=1$ a retum $\left[00^{},{ }^{} 1\right]$
clset
retum (appeadAtFrout(0″, bitStriags $(\mathrm{a}-1))+$ append.MtFrout(“1”, bitStrings(1-1)))
print (batStrings(1))
Afermetínset
def batStriags(n):
if $\mathrm{n}=0$ = retum |
if $\mathrm{n}=1:$ retum [0″, “1”]
return | digit bitstring for digit in bitStrings(1)
for bitstring in bitStrings(n-1)|
print (bathtrings(1))
Let $T(n)$ be the running time of binary $(n)$. Assume function print $f$ takes time $O(1)$.
$$T(n)=\left{\begin{array}{lr} c_{1} & \text { if } n<0 \ 2 T(n-1)+d, \text { otherwise } \end{array}\right.$$
Using Suberaction and Conquer Master theorem we get: $T(n)=O\left(2^{n}\right)$. This means the algorithm for generating bit-strings is optimal. Problem-4 Generate all the strings of length $n$ drawu from $0 . . k-1$.
Solution: Let us assume we keep current $k$-ary string in an array $A[0 . . n-1]$. Call function $k$-string $(n, k)$ :
def range Tol ist(k):
result – II
def range Tol ist(k):
result –
for i in range(0,k):
result.append(str(i))
retura result
for $i$ in range(0,k):
result.append(str(i))
return result
def baseKStrings $(\mathrm{n}, \mathrm{k})$ :

## 统计代写|数据结构作业代写data structure代考|Finding the length

Problem-6 Finding the length of connected cells of 1s (resions) in a mntrix of Os and 1s: Given a matrix, each of which may be 1 or 0 . The filled cells that are connected form a region. Two cells are said to be connected if they are adjacent to each other horizontally, vertically or diagonally. There may be several regions in the matrix. How do you find the largest region (in terms of number of cells) in the matrix?

Sample Input? 11000 Sample Output: 5 01100 00101 10001 01011
Solution
$\operatorname{def} \operatorname{getval}(\boldsymbol{A}, \mathrm{i}, \mathrm{j}, \mathrm{L}, \mathrm{H})$ !
if $(i<0$ or $i>-$ L or j<0 or $j>-H):$
return 0
else:
return Alillil
def findMaxBlock $\left(A, r, c, L_{\text {. }} H\right.$, sizc):
global maxsize
global cntart
if $(\mathrm{r}>-\mathrm{L}$ or $c>-\mathrm{H})$ :
return
cntart|r||c|-1
size $+-1$
if (size $>$ maxsize):
maxsize – size

$\mathrm{~ d i r e c t i o n – [ | – 1 , 0 ] , | – 1 , – 1 | , | 0 , – 1 ] , [ 1 , – 1 | , [ 1 , 0 ] , { 1 , 1 ] , | 0 , 1 | , | – 1 , 1 | |}$
for i in range(0,7):
newi – $r+$ direction[i]|이
val-getval (A, newi, new], L., H)
if (val>0 and (cutarr|newi][new] $\mid=-0)$ ):
findMaxBlock( $A$, newi, newj, L, H, size)
cutiurr $|r||c|-0$
def getMaxOnes(A, rmax, colmax):
global maxsize
global size
global cntarr
for $i$ in range $(0$, rax $)$ :
for $j$ in range(0,colnax):
if $(A|\mathrm{~A}| \mathrm{bl}-1)$ :
findMavRlork ( $\Lambda, i, j$, rnax, colmax, 0 )
return maxsize
$\mathrm{~ z a r r – | { 1 , 1 , 0 , 0 , 0 ] , | 0 , 1 , 1 , 0 , 1 | , [ 0 , 0 , 0 , 1 , 1 ] , [ 1 , 0 , 0 , 1 , 1 ] , { 0 , 1 , 0 , 1 , 1 ] |}$
$\max =5$

## 统计代写|数据结构作业代写data structure代考|Path finding problem

If we have reached the destination point
retum an array containing only the position of the destination clse

1. Mewe in the forwards diroction and cherk if this learle to a solution
2. If option a does uot work, then mone down
3. If either work, add the current position to the solution obtained at cither 1 or 2
def pathFinder(Matrix, position, N):

if position = $(\mathrm{N}-1, \mathrm{~N}-1)$ :
return ${(N-1, N-1) \mid$
$x, y=$ positicm
if $\mathrm{x}+1<\mathrm{N}$ and Matrix $|\mathrm{x}+1||\mathrm{y}|-1$ :
$a$ – pathFinder(Matrix $(x+1, y), N)$
if a !-None:
retum $|(x, y)|+a$
if $\mathrm{y}+1<\mathrm{N}$ and Matrix $[\mathrm{x}|| \mathrm{y}+1 \mid-1$ :
$b=p a r h F$ iader(Matrix , $(x+y+1), N)$
if $b$ !- None:
retum $|(\mathrm{x}, \mathrm{y})|+\mathrm{b}$
Matrix – $\lfloor 11,1,1,1,0],{0,1,0,1,0],[0,1,0,1,0],{0,1,0,0,0], \mid 1,1,1,1,1] \mid$
prisut (pathFinder(Matrix, $(0,0), 5)$ )

## 统计代写|数据结构作业代写data structure代考|Solutions

def appendAt Frout $(\mathrm {x}, 1 \ mathrm {j})$ return $\ mid \ mathrm {x +$ clemeat for clement in L] chef bitStrings(n): if $\ mathrm {n } = 0$ – retura $[1$ if $\ mathrm {a} = 1$ a retum $\ left [00 ^ { }, {} ^ } 1 \ right]$返回 | 位串中的数字位串 (1) 位串中的位串 (n-1) | 打印（浴巾（1））(\ mathrm {x}, 1 \ mathrm {j}) \ mid \ mathrm {x} + clemeat for clement in L] \ mathrm {n} = 0 – retura [1 \ mathrm {a} = 1 a retum $\ left [00 { clset retum (appeadAtFrout (0 ″, bitStriags (\ mathrm {a} -1))) + append.MtFrout (“1”, bitStrings (1-1))) print (batStrings (1)) Afermetínset def batStriags (n): 如果\mathrm {n} = 0 = 返回 | 如果\ mathrm {n} = 1:$ retum [0 ″, “1”](x,1j)
∣x+n=0[1
a=1clsetretum(appeadAtFrout(0″,bitStriagsíappend.MtFrout(“1”,bitStrings(1−1)))print(batStrings(1))AfermetínsetdefbatStriags(n):if=retum|if令 T(n) 为二进制 (n) 的运行时间。假设函数 print f 花费时间 O(1)。
$$T(n)=\left{\begin{array}{lr} c_{1} & \text { 如果 } n<0 \ 2 T(n-1)+d, \text { 否则 } \end{数组}\对。$$

## 广义线性模型代考

statistics-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。

## 统计代写|数据结构作业代写data structure代考|Format of a Recursive Function

statistics-lab™ 为您的留学生涯保驾护航 在代写数据结构data structure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。我们的专家在代写数据结构data structure方面经验极为丰富，各种代写数据结构data structure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|数据结构作业代写data structure代考|Format of a Recursive Function

A recursive function perfomus a task in part by callimg itself to perform the subtasks. At sonve point, the function encounters a subtask that it can perform without calling itself. This case, where the function does not recur, is called the base case. The former, where the fuaction calls itself to perform a subtask, is referred to as the recursive case. We can write all recursive functions using the format:
if(test for the base casc):
return some base case value
cliftest for aaother base case):
return sone oxher base case value

clse:
return (some work and then a recursive call)
As an example, consuder the factorial function: $n$ ! is the product of all integers between $n$ and 1 . The definition of recursive factorial looks like:
$$\begin{gathered} n !=1, \quad \text { if } n=0 \ n !=n=(n-1) ! \text { if } n=0 \end{gathered}$$
This definition can easily be converted to recursive implementation. Here the problem is determining the value of $n$ !, and the subproblem is determining the value of $(n-l)$. In the recursive case, when $n$ is greater than 1 , the function calls itself to determine the value of ( $n-l)$ ! and multiplies that with $n$.
In the base ease, when $n$ is 0 or 1 , the function simply retums 1 . This looks like the following:
$/ /$ calculates factorial of a positive integer
def factorial(n):
if $\mathrm{n}=0$ : retum 1
retum $n$ “factorial(n-1)
priat (fictomảal(6))

## 统计代写|数据结构作业代写data structure代考|Problems & Solutions

In this chapter we cover a few problems wath recursion and we will discuss the rest ia other chapters. By the time you complete reading the entire book, you will encouater many recursion problems.
Problem-1 Discuss Towers of Hanoi puzale.
Solution: The Towers of Hanoi is a mathematical puzzle. It consists of three rods (or pegs or towers) and a number of disks of different sizes which can slide onto any rod. The puzale starts with the disks on one rod in ascending order of size, the smallest at the top, thus making a conical shape. The objective of the puzzle is to move the entire stack to another rod, satisfying the following rules:

• Only one disk may be moved at a tine.
• Each move consists of taking the upper disk from one of the rods and sliding it onto another rod, on top of the other disks that may already be present on that rod.
• No disk may be placed on top of a smaller disk.
Algorithm:
• Mone the top $n-1$ disks from Source to Auxiliary tower,
• Move the $n^{\text {th }}$ disk from Source to Destination tower,
• Mone the $n-1$ disks from Auxiliary tower to Destination tower.
• Transfering the top $n-1$ disks from Source to Auxiliary tower can again be thought of as a fresh problem and can be solved in the sime manner. Once we solve Towers of Hanoi with three disks, we can solve it with any number of disks with the above ialgorithm.
def towersOHHanoi(numberOIDisks, startPeg-1, endPeg-3):
if numberOfDisks:
towersOHHanoi (numberOIDisks-1, startPeg, 6-startPeg-endPeg)
print (“Move disk \%d from peg \%id to peg \%d” \% (numberOfDisks, startPeg, endPeg))
towersOHHanoi (numberOIDisks-1, 6-stantPeg-endPeg, endPeg)
towersOHHanoi (numberOHDisks-1)

## 统计代写|数据结构作业代写data structure代考|What is Backtracking

Backtracking is an inproveruent of the brute force approach. It systematically searches for a solution to a problem anbong all available options. In backtracking, we stant with one possable option out of many avalable options and try to solve the problem if we are able to solve the problem with the selected move then we wall priat the solution clse we wall backurack and select some other option and try solve it. If thone if the options work out, we wall clain that there is no solution for the problem.

Backuracking is a form of recursion. The ustal scenario is that youn are faced with a number of optionas, and you must choose one of these. After you make your choice you will get a new set of options; just what set of options you get depends on what choice you nade. This procedure is repeated over and over until you reach a final state. If you made a good sequence of choices, your final state is a goal state; if you

didn’t, it isn’. Backtracking can be thotght of as a selective trec/graph traversal racthod. The tree is a way of representing sonse initial starting position (the root node) and a fiaal goal state (one of the leaves). Backtracking allows us to deal with satuations in which a raw brute-force approash woudd cxphode mto an impossible mumber of options to consaidcr. Backuncking is a sort of refincd brute force. At sach mode, we elimainate choices that are obwiously asot poscible and proceed to recursively checl only those that have potential.
$\mathrm{~ W h a t ‘ s ~ i n t e r e s t i n g ~ a h o u n t h a r k t r a r k i n g ~ i s ~ t h a t ~ w e ~ h a r k ~ m p ~ o n l y ~ a s ~ f a r ~ a s ~ a c e d e r t ~ t r ~ w e a r h ~ a ~ p o r e v i n u s ~ d o r i}$ alternative. In general, that will be at the most recent decision point. Eventually, more and nore of these decision points will have becn fully explored, and we will have to backtrack further asd further. If we backtrack all the way to our initial state and have explored all alternatives from there, we can conchude the particular problen is unsolvable. In such a case, we will have done all the work of the exhatstive recursion and known that there is no viable solution possible.

• Sonvetimes the best algorithm for a problem is to try all possibilities.
• This is always slow, but there are standard tools that can be uscd to help.
• Tools: algorithams for gcacrating basic objects, such as binary strings |2n possabilities for n-bit stringl. permatations
• Backtracking speeds the exhaustive search by pruaing.

## 统计代写|数据结构作业代写data structure代考|Format of a Recursive Function

if(test for the base casc):
return some base case value
cliftest for aaother base case):
return sone oxher base case value

clse:
return (一些工作，然后是递归调用)

n!=1, 如果 n=0 n!=n=(n−1)! 如果 n=0

//计算正整数
def factorial(n) 的阶乘：

1n“阶乘(n-1)
priat (fictomảal(6))

## 统计代写|数据结构作业代写data structure代考|Problems & Solutions

• 一个齿只能移动一个磁盘。
• 每次移动都包括从一根杆上取下上面的圆盘，然后将其滑到另一根杆上，在该杆上可能已经存在的其他圆盘的顶部。
• 任何磁盘都不能放在较小的磁盘上。
算法：
• 蒙顶n−1从源到辅助塔的磁盘，
• 移动nth 从源到目标塔的磁盘，
• 钱n−1从辅助塔到目标塔的磁盘。
• 转移顶部n−1从源到辅助塔的磁盘可以再次被认为是一个新问题，并且可以以同样的方式解决。一旦我们用三个圆盘解决了河内塔，我们就可以用上述算法用任意数量的圆盘来解决它。
def towersOHHanoi(numberOIDisks, startPeg-1, endPeg-3):
if numberOfDisks:
towersOHHanoi (numberOIDisks-1, startPeg, 6-startPeg-endPeg)
print (“将磁盘 \%d 从 peg \%id 移动到 peg \%d” \% (numberOfDisks, startPeg, endPeg))
towersOHHanoi (numberOIDisks-1, 6-stantPeg-endPeg, endPeg)
towersOHHanoi (numberOHDisks-1)

## 统计代写|数据结构作业代写data structure代考|What is Backtracking

Backuracking 是递归的一种形式。通常情况下，您面临许多选项，您必须选择其中之一。做出选择后，您将获得一组新选项；您获得的选项集取决于您做出的选择。一遍又一遍地重复此过程，直到达到最终状态。如果您做出了良好的选择顺序，那么您的最终状态就是目标状态；如果你

在H一种吨‘s 一世n吨和r和s吨一世nG 一种H这在n吨H一种rķ吨r一种rķ一世nG 一世s 吨H一种吨 在和 H一种rķ 米p 这nl是 一种s F一种r 一种s 一种C和d和r吨 吨r 在和一种rH 一种 p这r和在一世n在s d这r一世选择。一般来说，这将是最近的决策点。最终，越来越多的这些决策点将被充分探索，我们将不得不进一步回溯 asd。如果我们一直回溯到我们的初始状态并从那里探索了所有替代方案，我们可以推断特定问题是无法解决的。在这种情况下，我们将完成详尽递归的所有工作，并且知道没有可行的解决方案。

• Sonvetimes 解决问题的最佳算法是尝试所有可能性。
• 这总是很慢，但是有一些标准工具可以用来提供帮助。
• 工具：用于 gcacrating 基本对象的算法，例如二进制字符串 |n 位字符串 l 的 2n 种可能性。排列
• 回溯通过 pruaing 加速穷举搜索。

## 广义线性模型代考

statistics-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。