▍1. 新建文本文档
说明： 估算波动率的动态条件相关系数，衡量两个金融市场之间的风险溢出效应(Estimating the dynamic conditional correlation coefficient of volatility and measuring the Risk Spillover Effect between two financial markets)
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▍2. Arma-Garch-Copula-master
说明： 用R语言写出的copula-GARCH函数(copula-GARCH function using R language)
▍4. Copula
用R语言绘制copula的图分析两者相关性，可根据需求调整数值(Plot Gaussian copula in R)
▍5. Copula
说明： 用R语言绘制copula的图分析两者相关性，可根据需求调整数值(Plot Gaussian copula in R)
▍6. copula_0.5-7.tar
copula R语言，编程学习。享受copula学习的乐趣。R语言编程，copula代码(R copula)
▍7. 因子分析案例和R语言代码
说明： 因子分析:包括案例和对应的R语言代码，代码中地址需要自行修改后使用(Factor analysis: including a case and corresponding R language code, the address in the code needs to be modified by itself)
▍8. wine
葡萄酒数据集， 基于Wine数据集的数据分析报告 R语言+实验结果文档(Wine datasets Data Analysis Report R Language + Experimental Results Document Based on Wine Data Set)
▍9. wine
说明： 葡萄酒数据集， 基于Wine数据集的数据分析报告 R语言+实验结果文档(Wine datasets Data Analysis Report R Language + Experimental Results Document Based on Wine Data Set)
▍10. VineCopula_1.1-3
This program is a complete Vine-copula in R-package. It can be use to find correlation in multiple events, I use it for correlation between windfarms
▍12. midasr_0.6.tar
混频回归模型的r语言包，里边包括例题啥的。(The package of midas (mixed frequecncy), which includes the concrete code of some examples.)
▍13. did
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)
▍14. TOPSIS--R
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.)
▍15. 《深度学习精要(基于R语言)》高清中文版
说明： 本书重点介绍如何将R 语言和深度学习模型或深度神经网络结合起来，解决实 际的应用需求。全书共6 章，分别介绍了深度这习基础知识、训练预测模型、如何 防止过拟合、识别异常数据、训练深度预测模型以及调节和优化模型等内容。 本书适合了解机器学习概念和R语言并想要使用R提供的包来探索深度学习应 用的读者学习参考。(This book focuses on how to combine R language with deep learning model or deep neural network to solve the practical application requirements. There are six chapters in the book, which respectively introduce the basic knowledge of depth learning, training prediction model, how to prevent over fitting, identify abnormal data, training depth prediction model, adjustment and optimization model, etc. This book is suitable for readers who understand the concept of machine learning and R language and want to use the package provided by R to explore deep learning applications.)
▍16. 第三代神经网络
本文主要介绍深度学习以及复杂layman形式运算的深度网络。通过真实数据的实验，定量比较，证实（或证伪）深度神经网络理论在外汇交易中的优势。当前主要用途是分类，基于深度神经网络模型创建一个指标和一个EA，根据客户端/服务器的方式进行运作，并对它们进行测试。(This paper mainly introduces deep learning and deep network of complex layman form operations. Through real data experiments, quantitative comparison proves that (or falsified) deep neural network theory has the advantage in foreign exchange trading. The current main use is classification, based on a deep neural network model to create an indicator and a EA that operates on the client / server way and tests them.)
▍17. Time-Series
使用R语言进行股票数据时间序列分析，为《R and Data Mining》一书中Time Series一章的代码编写与分析(Using the R language to analyze stock time series data,R and Data Mining-Chapter Time Series code writing and analysis)
▍18. R
说明： 金融时间序列分析上证指数的GARCH模型R语言代码，可用于研究股票的波动性和预测。(The GARCH model R language code of the Shanghai Stock Exchange Index for financial time series analysis can be used to study the volatility and prediction of stocks.)
▍19. Rts
关于时间序列分析的一些比较简单的例子，有注释。使用R语言编写。(Some examples of time series in R)
▍20. R语言实战（第2版）中文
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.)
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