simD

Just a simulated dataset to illustrate the model. The success probability and the covariate have a non-linear relationship.

datasets

Markov chain Monte Carlo algorithms for non- and semi-parametric models: 1. Dirichlet process mixtures & 2. spike-slab for variable selection in mean/variance regression models.

Georgios Papageorgiou

BNSP

Bayesian Non- And Semi-Parametric Model Fitting

simD function

A data frame with 300 independent observations. Three numerical vectors contain information on<dl class="dl-horizontal">
 <dt><code>Y</code></dt><dd>number of successes.</dd>
 <dt><code>E</code></dt><dd>number of trials.</dd>
 <dt><code>X</code></dt><dd>explanatory variable.</dd>
 </dl>

Format

Simulated dataset — simD

A data frame with 300 independent observations. Three numerical vectors contain information on<dl class='dl-horizontal'>
 <dt><code>Y</code></dt><dd>number of successes.</dd>
 <dt><code>E</code></dt><dd>number of trials.</dd>
 <dt><code>X</code></dt><dd>explanatory variable.</dd>
 </dl>

simD: Simulated dataset

Description

Usage

Arguments

Format