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oglmx (version 3.0.0.0)

Estimation of Ordered Generalized Linear Models

Description

Ordered models such as ordered probit and ordered logit presume that the error variance is constant across observations. In the case that this assumption does not hold estimates of marginal effects are typically biased (Weiss (1997)). This package allows for generalization of ordered probit and ordered logit models by allowing the user to specify a model for the variance. Furthermore, the package includes functions to calculate the marginal effects. Wrapper functions to estimate the standard limited dependent variable models are also included.

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Version

Install

install.packages('oglmx')

Monthly Downloads

30

Version

3.0.0.0

License

GPL-2

Maintainer

Nathan Carroll

Last Published

May 5th, 2018

Functions in oglmx (3.0.0.0)

ologit.reg

Fit an ordered Logit model.
formula.oglmx

Obtain model formula for an oglmx object.
D_continuous.margin.mean_mean

Calculate derivatives of marginal effects for continuous variables.
D_discrete.margin_meanonly.mean

Calculate derivatives of marginal effects for binary variables.
InternalFunctions

Various functions not intended for user.
AIC.oglmx

Calculate Akaike Information Criterion
scoreMean

Calculate derivatives of loglikelihood
continuous.margin.mean

Calculate marginal effects for continuous variables.
McFaddensR2.oglmx

Calculate McFadden's R-Squared.
logLik.oglmx

Extract log likelihood value
discrete.margin_meanonly

Calculate marginal effects for binary variables.
oglmx-package

oglmx Package for estimation of ordered generalized linear models.
oglmx

Fit Ordered Generalized Linear Model.
getEtas

Construct ingredients for probability calculation.
margins.oglmx

Calculate marginal effects for oglmx objects.
oprobit.reg

Fit Ordered Probit Model.
summary.oglmx

Summarizing Ordered Discrete Outcome Model Fits
logit.reg

Fit Logit Model.
probit.reg

Fit Probit Model.
vcov.oglmx

Calculate Variance-Covariance Matrix for an oglmx Object