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

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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

## 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

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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。