simul_pois2


The same simulation setup is used as in <code><a rd-options="" href="/link/simul_pois1?package=pogit&version=1.1.0" data-mini-rdoc="pogit::simul_pois1">simul_pois1</a></code> but considers 
clustered observations. 10 regressors are generated, six of them continuous 
N(0,1)-variables and four binary with $p(x_i)=0.5$. 
The regression effects are set to <code>beta = {2,1,0.6,0,0,1.2,0,0,0.4,-0.2,0.3}</code>.
To simulate clustering, it is assumed that each of 
C=10 clusters is formed of 30 subjects and 10 random intercepts are generated 
from a normal distribution with zero mean and standard deviation 
$\theta$ = 0.1.


datasets

Bayesian variable selection for regression models of under-reported
count data as well as for (overdispersed) Poisson, negative binomal and
binomial logit regression models using spike and slab priors.

Michaela Dvorzak

pogit

Bayesian Variable Selection for a Poisson-Logistic Model

simul_pois2 function

A data frame with 300 rows and the following 12 variables: 
<dl>
 <dt><code>y</code></dt><dd>number of counts for each covariate pattern in each cluster</dd> <dt><code>cID</code></dt><dd>cluster ID of each count</dd> <dt><code>X.0</code></dt><dd>intercept</dd> <dt><code>X.1</code>, <code>X.2</code>, <code>X.3</code>, <code>X.4</code>, <code>X.5</code>, <code>X.6</code>, <code>X.7</code>, <code>X.8</code>, <code>X.9</code>, <code>X.10</code></dt><dd>covariates</dd> </dl>

simul_pois2: Simulated data set

Description

Usage

Arguments

Format

See Also