quantile reg estimate and test, python reticulate examples

.Rprofile

@@ -11,6 +11,7 @@ library(REconTools)
 library(formatR)
 
 # jointly use R and Python Together
+library(reticulate)
 
 # RMD Options
 options(knitr.duplicate.label = "allow")
@@ -19,7 +20,7 @@ options(bookdown.render.file_scope = FALSE)
 knitr::opts_chunk$set(fig.width=7, fig.height=4, fig.align="center")
 # knitr::opts_chunk$set(tidy.opts=list(width.cutoff=60), tidy=TRUE)
 knitr::opts_chunk$set(warning=FALSE, message=FALSE, cache=FALSE)
-opts_chunk$set(engine.path = "C:/ProgramData/Anaconda3/envs/wk_pyfan/python.exe")
+knitr::opts_chunk$set(engine.path = "C:/ProgramData/Anaconda3/envs/wk_pyfan/python.exe")
 
 # Output HTML or Latex
 if (knitr::is_latex_output()) {

README.md

@@ -8,7 +8,7 @@ Materials gathered from various [projects](https://fanwangecon.github.io/researc
 
 Bullet points show which [base R](https://www.rdocumentation.org/packages/base/versions/3.5.2), [tidyverse](https://www.tidyverse.org/) or other functions/commands are used to achieve various objectives. An effort is made to use only [base R](https://www.rdocumentation.org/packages/base/versions/3.5.2) and [tidyverse](https://www.tidyverse.org/) packages whenever possible to reduce dependencies. The goal of this repository is to make it easier to find/re-use codes produced for various projects.
 
-From other repositories: For dynamic borrowing and savings problems, see [Dynamic Asset Repository](https://fanwangecon.github.io/CodeDynaAsset/); For code examples, see also [Matlab Example Code](https://fanwangecon.github.io/M4Econ/) and [Stata Example Code](https://fanwangecon.github.io/Stata4Econ/); For intro econ with Matlab, see [Intro Mathematics for Economists](https://fanwangecon.github.io/Math4Econ/), and for intro stat with R, see [Intro Statistics for Undergraduates](https://fanwangecon.github.io/Stat4Econ/). See [here](https://github.com/FanWangEcon) for all of [Fan](https://fanwangecon.github.io/)'s public repositories.
+From other repositories: For dynamic borrowing and savings problems, see [MEconTools](https://fanwangecon.github.io/MEconTools/) and [Dynamic Asset Repository](https://fanwangecon.github.io/CodeDynaAsset/); For code examples, see also [Matlab Example Code](https://fanwangecon.github.io/M4Econ/), [Stata Example Code](https://fanwangecon.github.io/Stata4Econ/), [Python Example Code](https://fanwangecon.github.io/pyfan/); For intro econ with Matlab, see [Intro Mathematics for Economists](https://fanwangecon.github.io/Math4Econ/), and for intro stat with R, see [Intro Statistics for Undergraduates](https://fanwangecon.github.io/Stat4Econ/). See [here](https://github.com/FanWangEcon) for all of [Fan](https://fanwangecon.github.io/)'s public repositories.
 
 Please contact [FanWangEcon](https://fanwangecon.github.io/) for issues or problems.
 
@@ -205,6 +205,12 @@ Please contact [FanWangEcon](https://fanwangecon.github.io/) for issues or probl
 	+ Logit regression testing and prediction.
 	+ **stats**: *glm(as.formula(), data, family='binomial') + predict(rs, newdata, type = "response")*
 
+## 6.2  Quantile Regression
+
+1. [Quantile Regressions with Quantreg](https://fanwangecon.github.io/R4Econ/regnonlin/quantreg/htmlpdfr/fs_quantreg_intro.html): [**rmd**](https://github.com/FanWangEcon/R4Econ/blob/master/regnonlin/quantreg//fs_quantreg_intro.Rmd) \| [**r**](https://github.com/FanWangEcon/R4Econ/blob/master/regnonlin/quantreg/htmlpdfr/fs_quantreg_intro.R) \| [**pdf**](https://github.com/FanWangEcon/R4Econ/blob/master/regnonlin/quantreg/htmlpdfr/fs_quantreg_intro.pdf) \| [**html**](https://fanwangecon.github.io/R4Econ/regnonlin/quantreg/htmlpdfr/fs_quantreg_intro.html)
+	+ Quantile regression with continuous outcomes. Estimates and tests quantile coefficients.
+	+ **quantreg**: *rq(mpg ~ disp + hp + factor(am), tau = c(0.25, 0.50, 0.75), data = mtcars) + anova(rq(), test = "Wald", joint=TRUE) + anova(rq(), test = "Wald", joint=FALSE)*
+
 # 7  Optimization
 
 ## 7.1  Bisection
@@ -279,6 +285,12 @@ Please contact [FanWangEcon](https://fanwangecon.github.io/) for issues or probl
 	+ Modify markdown pounds hierarchy.
 	+ **r**: *file() + writeLines() + readLines() + close() + gsub()*
 
+## 11.2  Python with R
+
+1. [Python in R with Reticulate](https://fanwangecon.github.io/R4Econ/development/python/htmlpdfr/fs_python_reticulate.html): [**rmd**](https://github.com/FanWangEcon/R4Econ/blob/master/development/python//fs_python_reticulate.Rmd) \| [**r**](https://github.com/FanWangEcon/R4Econ/blob/master/development/python/htmlpdfr/fs_python_reticulate.R) \| [**pdf**](https://github.com/FanWangEcon/R4Econ/blob/master/development/python/htmlpdfr/fs_python_reticulate.pdf) \| [**html**](https://fanwangecon.github.io/R4Econ/development/python/htmlpdfr/fs_python_reticulate.html)
+	+ Use Python in R with Reticulate
+	+ **reticulate**: *py_config() + use_condaenv() + py_run_string() + Sys.which('python')*
+
 ----
 Please contact [![](https://img.shields.io/github/followers/fanwangecon?label=FanWangEcon&style=social)](https://github.com/FanWangEcon) [![](https://img.shields.io/twitter/follow/fanwangecon?label=%20&style=social)](https://twitter.com/fanwangecon) for issues or problems.
 

README_appendix.md

@@ -193,6 +193,12 @@
 	+ Logit regression testing and prediction.
 	+ **stats**: *glm(as.formula(), data, family='binomial') + predict(rs, newdata, type = "response")*
 
+### [Section 6.2 Quantile Regression][Quantile Regression] links
+
+1. [Quantile Regressions with Quantreg](https://fanwangecon.github.io/R4Econ/regnonlin/quantreg/htmlpdfr/fs_quantreg_intro.html): [**rmd**](https://github.com/FanWangEcon/R4Econ/blob/master/regnonlin/quantreg//fs_quantreg_intro.Rmd) \| [**r**](https://github.com/FanWangEcon/R4Econ/blob/master/regnonlin/quantreg/htmlpdfr/fs_quantreg_intro.R) \| [**pdf**](https://github.com/FanWangEcon/R4Econ/blob/master/regnonlin/quantreg/htmlpdfr/fs_quantreg_intro.pdf) \| [**html**](https://fanwangecon.github.io/R4Econ/regnonlin/quantreg/htmlpdfr/fs_quantreg_intro.html)
+	+ Quantile regression with continuous outcomes. Estimates and tests quantile coefficients.
+	+ **quantreg**: *rq(mpg ~ disp + hp + factor(am), tau = c(0.25, 0.50, 0.75), data = mtcars) + anova(rq(), test = "Wald", joint=TRUE) + anova(rq(), test = "Wald", joint=FALSE)*
+
 ## Optimization links
 
 ### [Section 7.1 Bisection][Bisection] links
@@ -266,3 +272,9 @@
 	+ Convert R Markdow File to R, PDF and HTML.
 	+ Modify markdown pounds hierarchy.
 	+ **r**: *file() + writeLines() + readLines() + close() + gsub()*
+
+### [Section 11.2 Python with R][Python with R] links
+
+1. [Python in R with Reticulate](https://fanwangecon.github.io/R4Econ/development/python/htmlpdfr/fs_python_reticulate.html): [**rmd**](https://github.com/FanWangEcon/R4Econ/blob/master/development/python//fs_python_reticulate.Rmd) \| [**r**](https://github.com/FanWangEcon/R4Econ/blob/master/development/python/htmlpdfr/fs_python_reticulate.R) \| [**pdf**](https://github.com/FanWangEcon/R4Econ/blob/master/development/python/htmlpdfr/fs_python_reticulate.pdf) \| [**html**](https://fanwangecon.github.io/R4Econ/development/python/htmlpdfr/fs_python_reticulate.html)
+	+ Use Python in R with Reticulate
+	+ **reticulate**: *py_config() + use_condaenv() + py_run_string() + Sys.which('python')*

README_pre.md

@@ -8,7 +8,7 @@ Materials gathered from various [projects](https://fanwangecon.github.io/researc
 
 Bullet points show which [base R](https://www.rdocumentation.org/packages/base/versions/3.5.2), [tidyverse](https://www.tidyverse.org/) or other functions/commands are used to achieve various objectives. An effort is made to use only [base R](https://www.rdocumentation.org/packages/base/versions/3.5.2) and [tidyverse](https://www.tidyverse.org/) packages whenever possible to reduce dependencies. The goal of this repository is to make it easier to find/re-use codes produced for various projects.
 
-From other repositories: For dynamic borrowing and savings problems, see [Dynamic Asset Repository](https://fanwangecon.github.io/CodeDynaAsset/); For code examples, see also [Matlab Example Code](https://fanwangecon.github.io/M4Econ/) and [Stata Example Code](https://fanwangecon.github.io/Stata4Econ/); For intro econ with Matlab, see [Intro Mathematics for Economists](https://fanwangecon.github.io/Math4Econ/), and for intro stat with R, see [Intro Statistics for Undergraduates](https://fanwangecon.github.io/Stat4Econ/). See [here](https://github.com/FanWangEcon) for all of [Fan](https://fanwangecon.github.io/)'s public repositories.
+From other repositories: For dynamic borrowing and savings problems, see [MEconTools](https://fanwangecon.github.io/MEconTools/) and [Dynamic Asset Repository](https://fanwangecon.github.io/CodeDynaAsset/); For code examples, see also [Matlab Example Code](https://fanwangecon.github.io/M4Econ/), [Stata Example Code](https://fanwangecon.github.io/Stata4Econ/), [Python Example Code](https://fanwangecon.github.io/pyfan/); For intro econ with Matlab, see [Intro Mathematics for Economists](https://fanwangecon.github.io/Math4Econ/), and for intro stat with R, see [Intro Statistics for Undergraduates](https://fanwangecon.github.io/Stat4Econ/). See [here](https://github.com/FanWangEcon) for all of [Fan](https://fanwangecon.github.io/)'s public repositories.
 
 Please contact [FanWangEcon](https://fanwangecon.github.io/) for issues or problems.
 

README_toc.md

@@ -189,6 +189,12 @@
 	+ Logit regression testing and prediction.
 	+ **stats**: *glm(as.formula(), data, family='binomial') + predict(rs, newdata, type = "response")*
 
+## 6.2  Quantile Regression
+
+1. [Quantile Regressions with Quantreg](https://fanwangecon.github.io/R4Econ/regnonlin/quantreg/htmlpdfr/fs_quantreg_intro.html): [**rmd**](https://github.com/FanWangEcon/R4Econ/blob/master/regnonlin/quantreg//fs_quantreg_intro.Rmd) \| [**r**](https://github.com/FanWangEcon/R4Econ/blob/master/regnonlin/quantreg/htmlpdfr/fs_quantreg_intro.R) \| [**pdf**](https://github.com/FanWangEcon/R4Econ/blob/master/regnonlin/quantreg/htmlpdfr/fs_quantreg_intro.pdf) \| [**html**](https://fanwangecon.github.io/R4Econ/regnonlin/quantreg/htmlpdfr/fs_quantreg_intro.html)
+	+ Quantile regression with continuous outcomes. Estimates and tests quantile coefficients.
+	+ **quantreg**: *rq(mpg ~ disp + hp + factor(am), tau = c(0.25, 0.50, 0.75), data = mtcars) + anova(rq(), test = "Wald", joint=TRUE) + anova(rq(), test = "Wald", joint=FALSE)*
+
 # 7  Optimization
 
 ## 7.1  Bisection
@@ -262,3 +268,9 @@
 	+ Convert R Markdow File to R, PDF and HTML.
 	+ Modify markdown pounds hierarchy.
 	+ **r**: *file() + writeLines() + readLines() + close() + gsub()*
+
+## 11.2  Python with R
+
+1. [Python in R with Reticulate](https://fanwangecon.github.io/R4Econ/development/python/htmlpdfr/fs_python_reticulate.html): [**rmd**](https://github.com/FanWangEcon/R4Econ/blob/master/development/python//fs_python_reticulate.Rmd) \| [**r**](https://github.com/FanWangEcon/R4Econ/blob/master/development/python/htmlpdfr/fs_python_reticulate.R) \| [**pdf**](https://github.com/FanWangEcon/R4Econ/blob/master/development/python/htmlpdfr/fs_python_reticulate.pdf) \| [**html**](https://fanwangecon.github.io/R4Econ/development/python/htmlpdfr/fs_python_reticulate.html)
+	+ Use Python in R with Reticulate
+	+ **reticulate**: *py_config() + use_condaenv() + py_run_string() + Sys.which('python')*

_bookdown.yml

@@ -70,6 +70,8 @@ rmd_files:
   - regnonlin/main.Rmd
   - regnonlin/logit/main.Rmd
   - regnonlin/logit/fs_logit_birhs.Rmd
+  - regnonlin/quantreg/main.Rmd
+  - regnonlin/quantreg/fs_quantreg_intro.Rmd
 
   - optimization/main.Rmd
   - optimization/root_bisect/main.Rmd
@@ -100,6 +102,8 @@ rmd_files:
   - development/inout/main.Rmd
   - development/inout/fs_text_save.Rmd
   - development/inout/fs_rmd_pdf_html.Rmd
+  - development/python/main.Rmd
+  - development/python/fs_python_reticulate.Rmd
 
   - README_appendix.md