--- A ---

AER包

Version: 1.2-9
Date: 2020-02-04
Title: Applied Econometrics with R
Authors@R: c(person(given = "Christian", family = "Kleiber", role = "aut", email = "Christian.Kleiber@unibas.ch"),
person(given = "Achim", family = "Zeileis", role = c("aut", "cre"), email = "Achim.Zeileis@R-project.org"))
Description:
Functions, data sets, examples, demos, and vignettes for the book
Christian Kleiber and Achim Zeileis (2008), Applied Econometrics with R, Springer-Verlag, New York.

AER包，是《Applied Econometrics with R》一书中的函数、数据集、例子、演示和简介。

• demos包含书中各章完整的R代码。
  • 查看demos列表：demo(package = "AER")。
  • 查看具体章节的demo：demo("Ch-Intro", package = "AER")
• 大约100个数据集。这些数据集取自顶级应用计量经济学期刊和教科书。
  • 查看数据集列表：data(package = "AER")
  • 教科书数据集提供该书所用的数据集、对应的章节和页码以及R代码：help("Greene2003", package = "AER")
• 新R函数。如 tobit()、 ivreg()、 dispersiontest()

--- E ---

Ecdat包

Version: 0.3-9
Date: 2020-11-02
Title: Data Sets for Econometrics
Author: Yves Croissant yves.croissant@let.ish-lyon.cnrs.fr and Spencer Graves
Depends: R (>= 3.5.0), Ecfun
Description: Data sets for econometrics, including political science.

一些经典数据集包。

--- H ---

Hmisc包

Version: 4.3-0
Title: Harrell Miscellaneous
Author: Frank E Harrell Jr f.harrell@vanderbilt.edu, with contributions from Charles Dupont and many others.
Description
Contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, importing and annotating datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of R objects to LaTeX and html code, and recoding variables.

包含许多用于数据分析、高级图形、实用操作的函数，如计算样本大小和功率、导入和注释数据集、填补缺失值、生成高级表、变量聚类、字符串操作、R对象转换为LaTeX和html代码，以及重新编码变量。

--- K ---

Knoema包

Title: Interface to the Knoema API
Version: 0.1.16
Date: 2018-05-11
Authors@R: c(person("Pavel Pimenov", role=c("aut", "cre"), email="pimenov@knoema.com"),
person("Ekaterina Chirkova", role="aut", email="chirkova@knoema.com"))
Description:
Using this package, users can access to the largest collection of public data and statistics on the Internet featuring about 2.5 billion time series from thousands of sources collected in 'Knoema' repository and use rich R calculations in order to analyze the data. Because data in 'Knoema' is time series data, 'Knoema' function offers data in a number of formats usable in R such as 'ts', 'xts' or 'zoo'. For more information about 'Knoema' API go to https://knoema.com/dev/docs.
URL: https://github.com/Knoema/knoema-r-driver
Knoema用户可以访问世界上最大的全球决策数据集合。Knoema拥有超过1.4k个来源发布的超过3.3b个时间序列。这个不断发展的数据库帮助捕捉新兴的社会，经济，金融，政治和行业特定的主题和趋势。
由于Knoema的数据是时间序列数据，所以Knoema提供多种R可用数据格式，如 'ts', 'xts' or 'zoo'。

---M---

modelsummary包

Title: Summary Tables and Plots for Statistical Models and Data:
Beautiful, Customizable, and Publication-Ready

Version: 0.9.1
Author:

• Vincent Arel-Bundock [aut, cre]
  (https://orcid.org/0000-0003-2042-7063),
• Joachim Gassen [ctb] (https://orcid.org/0000-0003-4364-2911),
• Nathan Eastwood [ctb],
• Nick Huntington-Klein [ctb] (https://orcid.org/0000-0002-7352-3991),
• Moritz Schwarz [ctb] (https://orcid.org/0000-0003-0340-3780),
• Benjamin Elbers [ctb] (0000-0001-5392-3448)

URL: https://vincentarelbundock.github.io/modelsummary/
Description: Create beautiful and customizable tables to summarize several
statistical models side-by-side. Draw coefficient plots, multi-level
cross-tabs, dataset summaries, balance tables (a.k.a. "Table 1s"), and
correlation matrices. This package supports dozens of statistical models,
and it can produce tables in HTML, LaTeX, Word, Markdown, PDF, PowerPoint,
Excel, RTF, JPG, or PNG. Tables can easily be embedded in 'Rmarkdown' or
'knitr' dynamic documents.

制作漂亮的可自定义的描述性统计表和统计模型结果表，包括系数图、交叉表、相关矩阵。这个包支持很多统计模型，可以生成HTML, LaTeX, Word, Markdown, PDF, PowerPoint, Excel, RTF, JPG，或PNG。 表也可以很容易地嵌入到“Rmarkdown”或“knitr”动态文档中。

--- R ---

rms包

Version: 5.1-4
Title: Regression Modeling Strategies
Author: Frank E Harrell Jr f.harrell@vanderbilt.edu
Description
Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. 'rms' is a collection of functions that assist with and streamline modeling. It also contains functions for binary and ordinal logistic regression models, ordinal models for continuous Y with a variety of distribution families, and the Buckley-James multiple regression model for right-censored responses, and implements penalized maximum likelihood estimation for logistic and ordinary linear models. 'rms' works with almost any regression model, but it was especially written to work with binary or ordinal regression models, Cox regression, accelerated failure time models, ordinary linear models, the Buckley-James model, generalized least squares for serially or spatially correlated observations, generalized linear models, and quantile regression.

rms，全称Regression Modeling Strategies，回归建模策略，通过储存拟合中增强型模型设计属性，进行回归建模、检验、估计、验证、作图、预测和排版。rms包是一个协助和简化建模的函数集。它的函数还包含二元logistic回归、有序logistic回归、各种分布的连续型Y的有序模型、Buckley-James 右截尾响应的多元回归模型，以及执行惩罚性最大似然估计的logistic模型和普通线性模型。
rms包适用于几乎所有的回归模型，但它尤其用来处理二元回归和有序回归模型、Cox回归、加速失效时间模型、普通线性模型，巴克利-詹姆斯模型，序列或空间相关观测的广义最小二乘法，广义线性模型和分位数回归。

report包

Title: Automated Reporting of Results and Statistical Models
Version: 0.3.5
Author:

• Dominique Makowski [aut, cre] (https://orcid.org/0000-0001-5375-9967,
  @Dom_Makowski),
• Daniel Lüdecke [aut] (https://orcid.org/0000-0002-8895-3206,
  @strengejacke),
• Mattan S. Ben-Shachar [aut] (https://orcid.org/0000-0002-4287-4801,
  @mattansb),
• Indrajeet Patil [aut] (https://orcid.org/0000-0003-1995-6531,
  @patilindrajeets),
• Rudolf Siegel [ctb] (https://orcid.org/0000-0002-6021-804X)

URL: https://easystats.github.io/report/
Description: The aim of the 'report' package is to bridge the gap between
R’s output and the formatted results contained in your manuscript.
This package converts statistical models and data frames into textual
reports suited for publication, ensuring standardization and quality
in results reporting.

report包将R输出的统计结果转化为科技论文的行文格式，确保结果报告的标准化和质量。