titanic

A dataset containing the number of survivals and the total number of persons by
passenger class, age group and gender.

datasets

Highly 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 boosting algorithms outlined in Fr<fc>hwirth-Schnatter S., Zens G., Wagner H. (2020) <arXiv:2011.06898>. The underlying implementation is written in C++.

Gregor Zens

Efficient Bayesian Models for Binary and Categorical Data

Sylvia Fr<fc>hwirth-Schnatter

Helga Wagner

Daniel F. Schmidt

Enes Makalic

titanic function

A data frame with 78 rows and 6 variables:<dl class="dl-horizontal">
 <dt>survived</dt><dd>number of passengers that survived</dd>
 <dt>total</dt><dd>number of total passengers</dd>
 <dt>intercept</dt><dd>an intercept</dd>
 <dt>pclass</dt><dd>passenger class (1 highest, 3 lowest)</dd>
 <dt>female</dt><dd>dummy for females</dd>
 <dt>age.group</dt><dd>age group indicator (0-5yrs, 5-10yrs, ...)</dd>
</dl>

Format

Grouped Titanic survival data. — titanic

A data frame with 78 rows and 6 variables:<dl class='dl-horizontal'>
 <dt>survived</dt><dd>number of passengers that survived</dd>
 <dt>total</dt><dd>number of total passengers</dd>
 <dt>intercept</dt><dd>an intercept</dd>
 <dt>pclass</dt><dd>passenger class (1 highest, 3 lowest)</dd>
 <dt>female</dt><dd>dummy for females</dd>
 <dt>age.group</dt><dd>age group indicator (0-5yrs, 5-10yrs, ...)</dd>
</dl>

titanic: Grouped Titanic survival data.

Description

Usage

Arguments

Format