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RCBR (version 0.5.9)

Random Coefficient Binary Response Estimation

Description

Nonparametric maximum likelihood estimation methods for random coefficient binary response models and some related functionality for sequential processing of hyperplane arrangements. See J. Gu and R. Koenker (2020) .

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Version

Install

install.packages('RCBR')

Monthly Downloads

188

Version

0.5.9

License

GPL (>= 2)

Maintainer

Roger Koenker

Last Published

November 16th, 2020

Functions in RCBR (0.5.9)

GK.control

Control parameters for Gautier-Kitamura bivariate random coefficient binary response

NICER

New Incremental Cell Enumeration (in) R

Current Status Linear Regression

NICERd

New (Accelerated) Incremental Cell Enumeration (in) R

bounds.KW2

Prediction of Bounds on Marginal Effects

KWDual

Dual optimization for Kiefer-Wolfowitz problems

KW.control

Control parameters for NPMLE of bivariate random coefficient binary response

neighbours

Check Neighbouring Cell Counts

polycount

Check Cell Count for degenerate hyperplane arrangements

Horowitz93

Horowitz (1993) Modal Choice Data

predict.KW2

Prediction of Marginal Effects

Identify crossed polygons from existing cells when adding a new line (works only for dim = 2)

witness

Find witness point

GH.se

Current Status Linear Regression Standard Errors

rcbr.fit.GK

Gautier and Kitamura (2013) bivariate random coefficient binary response

predict.GK

Prediction of Marginal Effects

rcbr.fit.KW2

NPMLE fitting for random coefficient binary response model

rcbr.fit

Fitting of Random Coefficient Binary Response Models

rcbr.fit.KW1

NPMLE fitting for the Cosslett random coefficient binary response model

prcbr

Profiling estimation methods for RCBR models

rcbr

Estimation of Random Coefficient Binary Response Models