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RPtests  

Goodness of Fit Tests for High-Dimensional Linear Regression Models
View on CRAN: Click here


Download and install RPtests package within the R console
Install from CRAN:
install.packages("RPtests")

Install from Github:
library("remotes")
install_github("cran/RPtests")

Install by package version:
library("remotes")
install_version("RPtests", "0.1.5")



Attach the package and use:
library("RPtests")
Maintained by
Rajen Shah
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-06-20
Latest Update: 2021-07-10
Description:
Performs goodness of fits tests for both high and low-dimensional linear models. It can test for a variety of model misspecifications including nonlinearity and heteroscedasticity. In addition one can test the significance of potentially large groups of variables, and also produce p-values for the significance of individual variables in high-dimensional linear regression.
How to cite:
Rajen Shah (2016). RPtests: Goodness of Fit Tests for High-Dimensional Linear Regression Models. R package version 0.1.5, https://cran.r-project.org/web/packages/RPtests. Accessed 28 Jan. 2025.
Previous versions and publish date:
0.1.0 (2016-06-20 20:33), 0.1.1 (2016-10-04 14:35), 0.1.2 (2016-11-07 21:07), 0.1.3 (2017-01-27 10:17), 0.1.4 (2017-04-03 17:30)
Other packages that cited RPtests R package
View RPtests citation profile
Other R packages that RPtests depends, imports, suggests or enhances
Complete documentation for RPtests
Functions, R codes and Examples using the RPtests R package
Some associated functions: RPtest . RPtest_single . pval . sparse_proj . sqrt_lasso . 
Some associated R codes: RPtest.R . RPtest_single.R . RcppExports.R . projections.R . pvals.R . resid_gen.R . sqrt_lasso.R . test_funcs.R .  Full RPtests package functions and examples
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