RPtests: Goodness of Fit Tests for High-Dimensional Linear Regression Models

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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.

Author
Rajen Shah [aut, cre], Peter Buhlmann [aut]
Date of publication
2016-11-07 21:07:38
Maintainer
Rajen Shah <r.shah@statslab.cam.ac.uk>
License
GPL (>= 2)
Version
0.1.2
URLs

View on CRAN

Man pages

pval
Compute p-values for 'RPtest' output
RPtest
Goodness of fit tests for potentially high-dimensional linear...
RPtest_single
Test significance of single predictors
sparse_proj
Sparse projections using the square-root Lasso
sqrt_lasso
Square-root Lasso regression

Files in this package

RPtests
RPtests/src
RPtests/src/Aux_functions.cpp
RPtests/src/RcppExports.cpp
RPtests/NAMESPACE
RPtests/R
RPtests/R/RPtest_single.R
RPtests/R/resid_gen.R
RPtests/R/projections.R
RPtests/R/RcppExports.R
RPtests/R/pvals.R
RPtests/R/RPtest.R
RPtests/R/test_funcs.R
RPtests/R/sqrt_lasso.R
RPtests/MD5
RPtests/DESCRIPTION
RPtests/man
RPtests/man/RPtest_single.Rd
RPtests/man/pval.Rd
RPtests/man/sqrt_lasso.Rd
RPtests/man/sparse_proj.Rd
RPtests/man/RPtest.Rd