R语言copula

说明：  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)

说明：  R Programming implementation of panel smoothing threshold regression model

ADS-B接收，采用PlutoSDR板卡，基于matlab开发(ADS-B receives, uses PlutoSDR card, develops based on MATLAB)

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)

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)

说明：  进行了常微分方程的建立，并模拟出经典的SIR模型曲线(The ordinary differential equation is established and the classical SIR model curve is simulated)

说明：  数据集实体文件名称：中国降水日值0.5°×0.5°格点数据集文件命名由数据集代码（SURF_CLI_CHN_PRE_DAY_GRID_0.5）、年月日标识（YYYYMMDD）组成。具体形式：SURF_CLI_CHN_PRE_DAY_GRID_0.5-YYYYMMDD.TXT(Specific form:SURF_CLI_CHN_PRE_DAY_GRID_0.5-YYYYMMDD.TXT)

中国地面气候资料日值数据集(V3.0)处理程序，可以用来处理中国气象数据网上的气象数据(China surface climate data daily data set (V3.0) processing program can be used to process meteorological data on China Meteorological data online.)

说明：  制作pcoa、饼图、venn图、热图、柱状图的脚本，可直接改参数使用，内有注释，适用于微生物多样性(the Script to make PCOA)

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)