program

A dataset containing the choice among general program, vocational program and academic program for 200 high school students as well as some explanatory
variables.

datasets

Efficient Bayesian implementations of probit, logit, multinomial logit and binomial logit models. Functions for plotting and tabulating the estimation output are available as well. Estimation is based on Gibbs sampling where the Markov chain Monte Carlo algorithms are based on the latent variable representations and marginal data augmentation algorithms described in "Gregor Zens, Sylvia Frühwirth-Schnatter & Helga Wagner (2023). Ultimate Pólya Gamma Samplers – Efficient MCMC for possibly imbalanced binary and categorical data, Journal of the American Statistical Association <doi:10.1080/01621459.2023.2259030>".

Gregor Zens

Efficient Bayesian Algorithms for Binary and Categorical Data
Regression Models

Sylvia Frühwirth-Schnatter

Helga Wagner

program function

A data frame with 200 rows and 5 variables:<dl>
 <dt>program</dt>
<dd>a vector of program choices</dd> <dt>intercept</dt>
<dd>an intercept term</dd> <dt>female</dt>
<dd>binary indicator for female students</dd> <dt>ses</dt>
<dd>socioeconomic status, 1 is lowest</dd> <dt>write</dt>
<dd>writing score of student</dd>
</dl>

Format

Students program choices. — program

A data frame with 200 rows and 5 variables:<dl>
 <dt>program</dt>
<dd>a vector of program choices</dd>

 <dt>intercept</dt>
<dd>an intercept term</dd>

 <dt>female</dt>
<dd>binary indicator for female students</dd>

 <dt>ses</dt>
<dd>socioeconomic status, 1 is lowest</dd>

 <dt>write</dt>
<dd>writing score of student</dd>


</dl>

program: Students program choices.

Description

Usage

Arguments

Format