Learn R Programming

AFR

The goal of AFR is to …

Installation

You can install the development version of AFR like so:

# FILL THIS IN! HOW CAN PEOPLE INSTALL YOUR DEV PACKAGE?

Example

This is a basic example which shows you how to solve a common problem:

library(AFR)
#> Registered S3 method overwritten by 'quantmod':
#>   method            from
#>   as.zoo.data.frame zoo
## basic example code

What is special about using README.Rmd instead of just README.md? You can include R chunks like so:

summary(cars)
#>      speed           dist       
#>  Min.   : 4.0   Min.   :  2.00  
#>  1st Qu.:12.0   1st Qu.: 26.00  
#>  Median :15.0   Median : 36.00  
#>  Mean   :15.4   Mean   : 42.98  
#>  3rd Qu.:19.0   3rd Qu.: 56.00  
#>  Max.   :25.0   Max.   :120.00

You’ll still need to render README.Rmd regularly, to keep README.md up-to-date. devtools::build_readme() is handy for this.

You can also embed plots, for example:

In that case, don’t forget to commit and push the resulting figure files, so they display on GitHub and CRAN.

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Version

Install

install.packages('AFR')

Monthly Downloads

482

Version

0.3.8

License

GPL-2

Maintainer

Sultan Zhaparov

Last Published

March 2nd, 2026

Functions in AFR (0.3.8)

reg_plot

Regression forecast plot
reg_test

Test for detecting violation of Gauss-Markov assumptions.
regsel_f

Regressors selection
pct4

Transforming time-series data to stationary
pt_multi

Pluto-Tasche method for multi-year probability of default (PD) analysis
dec_plot

Decomposition plot
bp

Breusch-Pagan test
finratKZ

finratKZ dataset
gq

Godfrey-Quandt test
difflog

Transforming time-series data to stationary
HP

Hodrick-Prescott filter for time series data
bg

Breusch-Godfrey test [BG test]
pct1

Transforming time-series data to stationary
pt_one

Pluto-Tasche method for one-year probability of default (PD) analysis
opt_size

Necessary size of the time-series dataset
ols_test_normality

Test for normality Test for detecting violation of normality assumption.
corsel

Multicollinearity test
check_betas

All possible regression variable coefficients.
checkdata

Preliminary data check for errors
vif_reg

VIF by variable
macroKZ

macroKZ dataset