RPtests: Goodness of Fit Tests for High-Dimensional Linear Regression Models
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.
- Rajen Shah [aut, cre], Peter Buhlmann [aut]
- Date of publication
- 2016-10-04 14:35:10
- Rajen Shah <firstname.lastname@example.org>
- GPL (>= 2)
- Compute p-values for 'RPtest' output
- Goodness of fit tests for potentially high-dimensional linear...
- Test significance of single predictors
- Sparse projections using the square-root Lasso
- Square-root Lasso regression
Files in this package