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• 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

## 数学代写|图论作业代写Graph Theory代考|Tournaments Revisited

We began Chapter 1 by introducing tournaments as an example of graph modeling. Recall that a tournament is a complete graph where each edge has been assigned a specific direction. As we have just spent considerable energy investigating methods for finding hamiltonian cycles on complete graphs, it is natural to wonder if these same ideas can be applied to tournaments.

First, consider the two tournaments shown below. Their underlying graph is $K_5$, which we know has $4 !=24$ unique hamiltonian cycles with a specific reference point. But if we are now required to follow the direction of an arc in the tournament, could we still find a hamiltonian cycle?

The tournament $T_1$ on the left has a hamiltonian cycle, given by $a e b c d a$, whereas the tournament $T_2$ on the right cannot have a hamiltonian cycle since $a$ has in-degree $\operatorname{deg}^{-}(a)=0$ and every vertex along a cycle must have nonzero in-degree and out-degree. But is this condition enough? Hopefully we have seen enough of the complexity surrounding hamiltonian graphs to suspect there is far more to it than just nonzero degrees. In fact, the tournament $T_3$ shown on the left below has degree sequence $1,1,1,4,4,4$ and yet no hamiltonian cycle can exist since if a cycle must exit vertices $c, d$, and $e$ then $\operatorname{arcs} c e, d c$, and $e d$ must all be included, which creates a subcycle, as shown on the right.

## 数学代写|图论作业代写Graph Theory代考|Shortest Paths

The shortest way to travel between two locations is perhaps one of the oldest questions. As any mathematics student knows, the answer to this question is a line. But this relies on an $x y$-plane with no barriers to traveling in a straight line. What happens when you must restrict yourself to an existing structure, such as roadways or rail lines? This problem can be described in graph theoretic terms as the search for a shortest path on a weighted graph. Recall that a path is a sequence of vertices in which there is an edge between consecutive vertices and no vertex is repeated. As with the algorithms for the Traveling Salesman Problem, the weight associated to an edge may represent more than just distance (e.g., cost or time) and the shortest path really indicates the path of least total weight.

As with the previous two topics in this chapter, our study of shortest paths can be traced to a specific moment of time. In 1956 Edsger W. Dijkstra proposed the algorithm we are about to study not out of necessity for finding a shortest route, but rather as a demonstration of the power of a new “automatic computer” at the Mathematical Centre in Amsterdam. The goal was to have a question easily understood by a general audience while also allowing for audience participation in determining the inputs of the algorithm. In Dijkstra’s own words “the demonstration was a great success” [23]. Perhaps more surprising is how important this algorithm would become to modern societyalmost every GIS (Geographic Information System, or mapping software) uses a modification of Dijkstra’s Algorithm to provide directions. In addition, Dijkstra’s Algorithm provid studies in epidemiology.

Note, we will only investigate how to find a shortest path since determining if a shortest path exists is quickly answered by simply knowing if the graph is connected. The following section will consider implications of shortest paths.

# 图论代考

## 有限元方法代写

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## 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。

assignmentutor™您的专属作业导师
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