R

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R语言编程学习，copula函数数据编程分析。相关性分析，R语言的应用(R Copula)

很好用的代码 简单操作 且是用R语言编写 真的很好用啊( Conceptually, this is a good model, but all too often people actually implement their code this way.)

说明：  spei的R语言计算版本 用于计算干旱指数spei(R language computing version of spei)

主要是利用r语言做简单线性回归，一元线性回归(use r language to solve simple ols)

通过本书，读者不仅能掌握使用R及相关算法包来快速解决实际问题的方法，而且能从实际问题分析入手，到利用R进行求解，以及对挖掘结果进行分析的全面训练(Through this book, readers can not only master the method of using R and relevant algorithm packages to quickly solve practical problems, but also start from the analysis of practical problems to the comprehensive training of using R to solve problems and analyzing mining results)

该书是一本较好的R语言编程书籍，从认识到实战，手把手教你如何使用R语言进行数据分析、挖掘、画图等等。(This book is a good R language programming book, from understanding to actual combat, teach you how to use R language data analysis, mining, drawing and so on.)

利用R语言SEM程序包进行通径分析，简单易学，容易上手(SEM path analysis model)

双重差分估计 双重差分模型（difference-in-difference，DID）近年来多用于计量经济学中对于公共政策或项目实施效果 的定量评估。 通常大范围的公共政策有别于普通科研性研究，难以保证对于政策实施组和对照组在样本分配上的完全随机。非随机分配政策实施组和对照组的试验称为自然试验（naturaltrial），此类试验存在较显著的特点，即不同组间样本在政策实施前可能存在事前差异，仅通过单一前后对比或横向对比的分析方法会忽略这种差异，继而导致对政策实施效果的有偏估计。(Quantitative evaluation of policy or project implementation effect. Generally, a wide range of public policies is different from general scientific research, and it is difficult to ensure that the sample allocation for the policy implementation group and the control group is completely random. The non-randomly assigned policy implementation group and the control group are called natural trials, which have significant characteristics, i.e. there may be prior differences between the different groups of samples before the implementation of the policy, and this difference will be ignored only through a single pre-and post-comparison or horizontal comparison analysis method, which leads to the policy. Biased estimation of implementation)

计算CVAR 条件下的最有权重，主要针对股票收益率进行分析(compute the optimal weight under CVAR condition)