# 统计代写|R语言代写R language代考|FOR6934

#### Doug I. Jones

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R是一种用于统计计算和图形的编程语言，由R核心团队和R统计计算基金会支持。R由统计学家Ross Ihaka和Robert Gentleman创建，在数据挖掘者和统计学家中被用于数据分析和开发统计软件。用户已经创建了软件包来增强R语言的功能。

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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
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## 统计代写|R语言代写R language代考|Matrices and multidimensional arrays

Vectors have a single dimension, and, as we saw above, we can query their length with method length(). Matrices have two dimensions, which can be queried with dim(), nco1 () and nrow(). R arrays can have any number of dimensions, even a single dimension, which can be queried with method dim(). As expected is.vector(), is.matrix() and is.array() can be used to query the class.

We can create a new matrix using the matrix() or as.matrix() constructors. The first argument of matrix() is a vector. In the same way as vectors, matrices are homogeneous, all elements are of the same type.

When a vector is converted to a matrix, R’s default is to allocate the values in the vector to the matrix starting from the leftmost column, and within the column, down from the top. Once the first column is filled, the process continues from the top of the next column, as can be seen above. This order can be changed as you will discover in the playground below.

Subscripting of matrices and arrays is consistent with that used for vectors; we only need to supply an indexing vector, or leave a blank space, for each dimension. A matrix has two dimensions, so to access any element or group of elements, we use two indices. The only complication is that there are two possible orders in which, in principle, indexes could be supplied. In R, indexes for matrices are written “row first.” In simpler words, the first index value selects rows, and the second one, columns.Remind yourself of how indexing of vectors works in R (see section $2.10$ on page 45 ). We will now apply the same rules in two dimensions.

## 统计代写|R语言代写R language代考|Factors

Factors are used to indicate categories, most frequently the factors describing the treatments in an experiment, or categories in a survey. They can be created either from numerical or character vectors. The different possible values are called levels. Normal factors created with factor() are unordered or categorical. R also supports ordered factors that can be created with function ordered().

The labels (“names”) of the levels can be set when the factor is created. In this case, when calling factor (), parameters 1evels and 1 abe1s should both be passed a vector as argument, with levels and matching labels in the same position in the two vectors. The argument passed to levels determines the order of the levels based on their old names or values, and the argument passed to labels gives new names to the levels.

It is always preferable to use meaningful labels for levels, although it is also possible to use numbers.

In the examples above we passed a numeric vector or a character vector as an argument for parameter $\mathrm{x}$ of function factor(). It is also possible to pass a factor as an argument for parameter $\mathbf{x}$. We use indexing with a test returning a logical vector to extract all “controls.” We use function levels() to look at the levels of the factors.

It can be seen above that subsetting does not drop unused factor levels, and that factor () can be used to explicitly drop the unused factor levels. Converting factors into numbers is not intuitive, even in the case where a factor was created from a numeric vector.

# R语言代写

## 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。

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