RRI (version 1.1)

Residual Randomization Inference for Regression Models

Description

Testing and inference for regression models using residual randomization methods. The basis of inference is an invariance assumption on the regression errors, e.g., clustered errors, or doubly-clustered errors.

Copy Link

Version

Install

install.packages('RRI')

Monthly Downloads

188

Version

1.1

License

GPL-2

Maintainer

Panos Toulis

Last Published

December 19th, 2019

Functions in RRI (1.1)

rrinf

Generic residual randomization confidence intervals

rrinf_clust

Residual randomization inference based on cluster invariances

rrtest

Generic residual randomization test

rrtest_clust

Residual randomization test under cluster invariances

get_clustered_eps

Calculate residuals restricted under H0

rrinfBase

Generic residual randomization inference This function provides the basis for all other rrinf* functions.

Checks whether the input model is valid.

r_test_c

Residual randomization test

OLS_c

Fast least squares

out_pval

Calculates p-value or test decision

restricted_OLS_c

Fast least squares with linear constraint

example_clustering

An example clustering object. A clustering is a List that splits indexes 1..#num_datapoints to clusters. Each List element corresponds to one cluster. The clustering is not necessarily a partition but it usually is.

example_model

Example regression model and H0.