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SemiParBIVProbit (version 3.2-12.1)

Semiparametric Bivariate Probit Modelling

Description

Routine for fitting bivariate probit models with semiparametric predictors (including linear and nonlinear effects) in the presence of correlated error equations, endogeneity, sample selection or partial observability. Bivariate copula models are also supported.

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Version

Install

install.packages('SemiParBIVProbit')

Monthly Downloads

95

Version

3.2-12.1

License

GPL (>= 2)

Maintainer

Giampiero Marra

Last Published

November 12th, 2014

Functions in SemiParBIVProbit (3.2-12.1)

SemiParBIVProbit

Semiparametric Bivariate Probit Modelling

print.SemiParBIVProbit

Print a SemiParBIVProbit object

Adjustment for the covariance matrix of the parameter estimates from a SemiParBIVProbit model fitted to complex survey data.

Estimated overall prevalence from sample selection models

Lagrange Multiplier Test (Score Test)

Some convergence diagnostics

Internal Function

SemiParBIVProbit.fit.post

Internal Function

Internal Function

Internal Function

Internal Function

logLik.SemiParBIVProbit

Extract the log likelihood for a fitted SemiParBIVProbit

SemiParBIVProbitObject

Fitted SemiParBIVProbit object

plot.SemiParBIVProbit

SemiParBIVProbit plotting

Internal Function

summary.SemiParBIVProbit

SemiParBIVProbit summary

predict.SemiParBIVProbit

Prediction from a fitted SemiParBIVProbit model

SemiParBIVProbit-package

Semiparametric Bivariate Probit Modelling

SemiParBIVProbit.fit

Internal Function

Internal Function

print.summary.SemiParBIVProbit

Print a summary.SemiParBIVProbit object

Internal Function

Print an est.prev object

Internal Function

Adjustment for the covariance matrix of the parameter estimates from a fitted SemiParBIVProbit model

VuongClarke.bcm

Vuong and Clarke tests

Internal Function

Print an AT object

Average treatment effect of a binary endogenous variable