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RCBR

Random Coefficient Binary Response Estimation

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) <DOI:10.1080/01621459.2020.1802284>.

Functions (23)

Current Status Linear Regression

Current Status Linear Regression Standard Errors

Control parameters for Gautier-Kitamura bivariate random coefficient binary response

Horowitz (1993) Modal Choice Data

Control parameters for NPMLE of bivariate random coefficient binary response

Dual optimization for Kiefer-Wolfowitz problems

New Incremental Cell Enumeration (in) R

New (Accelerated) Incremental Cell Enumeration (in) R

Prediction of Bounds on Marginal Effects

Check Neighbouring Cell Counts

Plot a GK object

Plot a KW2 object

Check Cell Count for degenerate hyperplane arrangements

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

Profiling estimation methods for RCBR models

Prediction of Marginal Effects

predict.KW2

Prediction of Marginal Effects

rcbr

Estimation of Random Coefficient Binary Response Models

Fitting of Random Coefficient Binary Response Models

rcbr.fit.GK

Gautier and Kitamura (2013) bivariate random coefficient binary response

rcbr.fit.KW1

NPMLE fitting for the Cosslett random coefficient binary response model

rcbr.fit.KW2

NPMLE fitting for random coefficient binary response model

Find witness point

RCBR

Random Coefficient Binary Response Estimation

v0.5.9

GPL (>= 2)

Authors

Roger Koenker [aut, cre], Jiaying Gu [aut]

Initial release

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