plot.bdw

This function generates several diagnostics plots from a MCMC object of class 'bdw'

 HPD interval

A Bayesian regression model for discrete response, where the conditional distribution is modelled via a discrete Weibull distribution. This package provides an implementation of Metropolis-Hastings and Reversible-Jumps algorithms to draw samples from the posterior. It covers a wide range of regularizations through any two parameter prior. Examples are Laplace (Lasso), Gaussian (ridge), Uniform, Cauchy and customized priors like a mixture of priors. An extensive visual toolbox is included to check the validity of the results as well as several measures of goodness-of-fit.

Hamed Haselimashhadi

BDWreg

Bayesian Inference for Discrete Weibull Regression

plot.bdw function

<dl> <dt>x</dt>
<dd>The object containing the MCMC results of class 'bdw'.</dd> <dt>est</dt>
<dd>The statistic that is used to estimate parameters from marginal densities. The default is 'mode'.</dd> <dt>prob</dt>
<dd>A numerical value in (0 , 1). Corresponding probability for Highest Posterior Density (HPD) interval.</dd> <dt>adj</dt>
<dd>A positive value. Measure of smoothness for densities. A higher value results in smoother density plots.</dd> <dt>r.outliers</dt>
<dd>Logical flag. If TRUE, a preprocessing procedure removes the outliers before showing the results.</dd> <dt>density</dt>
<dd>Logical flag. If TRUE, a density plot accompanies the HPD intervals.</dd> <dt>exc.tun</dt>
<dd>Logical flag. If TRUE and penalized=TRUE, the penalty parameter is excluded from the plots.</dd><dt>...</dt>
<dd>Other parameters that can be passed to standard plot() function.</dd></dl>

Arguments

Hamed Haselimashhadi &lt;hamedhaseli@gmail.com&gt;

Author

Plot a MCMC object of class 'bdw' — plot.bdw

<dl>

 <dt>x</dt>
<dd>The object containing the MCMC results of class 'bdw'.</dd>

 <dt>est</dt>
<dd>The statistic that is used to estimate parameters from marginal densities. The default is 'mode'.</dd>

 <dt>prob</dt>
<dd>A numerical value in (0 , 1). Corresponding probability for Highest Posterior Density (HPD) interval.</dd>

 <dt>adj</dt>
<dd>A positive value. Measure of smoothness for densities. A higher value results in smoother density plots.</dd>

 <dt>r.outliers</dt>
<dd>Logical flag. If TRUE, a preprocessing procedure removes the outliers before showing the results.</dd>

 <dt>density</dt>
<dd>Logical flag. If TRUE, a density plot accompanies the HPD intervals.</dd>

 <dt>exc.tun</dt>
<dd>Logical flag. If TRUE and penalized=TRUE, the penalty parameter is excluded from the plots.</dd>

<dt>...</dt>
<dd>Other parameters that can be passed to standard plot() function.</dd>

</dl>

plot.bdw: Plot a MCMC object of class 'bdw'

Description

Usage

Arguments

Author

See Also

Examples