rVIB

the number of observations. If <code>length(n)</code> &gt; 1, the length is taken to be the number required.

the mean parameter. It must lie in (0, 1).

the precision parameter. It must be a positive real value.

the mixing weight. It must lie in (0, 1).

the extent of the variance inflation. It must lie in (0, 1).

The function randomly generates values from the variance-inflated beta distribution.

Functions to fit regression models for bounded responses (e.g., proportions and rates) and binomial data. Available models are the flexible beta (Migliorati, S., Di Brisco, A. M., Ongaro, A. (2018) <doi:10.1214/17-BA1079>), the variance-inflated beta (Di Brisco, A. M., Migliorati, S., Ongaro, A. (2020) <doi:10.1177/1471082X18821213>), the beta (Ferrari, S.L.P., and Cribari-Neto, F. (2004) <doi:10.1080/0266476042000214501>), the flexible beta-binomial (Ascari, R. and Migliorati, S. (2021) <doi:10.1002/sim.9005>), the beta-binomial, and the binomial one. Inference is dealt with a Bayesian approach based on the Hamiltonian Monte Carlo (HMC) algorithm (Gelman, A.; Carlin, J. B.; Stern, H. S. and Rubin, D. B. (2014) <doi:10.1201/b16018>). Besides, functions to compute residuals, posterior predictives, goodness-of-fit measures, convergence diagnostics, and graphical representations are provided.

Roberto Ascari

FlexReg

Regression Models for Bounded Responses

rVIB function

<dl><dt>n</dt>
<dd>the number of observations. If <code>length(n)</code> &gt; 1, the length is taken to be the number required.</dd>
<dt>mu</dt>
<dd>the mean parameter. It must lie in (0, 1).</dd>
<dt>phi</dt>
<dd>the precision parameter. It must be a positive real value.</dd>
<dt>p</dt>
<dd>the mixing weight. It must lie in (0, 1).</dd>
<dt>k</dt>
<dd>the extent of the variance inflation. It must lie in (0, 1).</dd></dl>

Arguments

Random generation from the variance-inflated beta distribution — rVIB

<dl>

<dt>n</dt>
<dd>the number of observations. If <code>length(n)</code> &gt; 1, the length is taken to be the number required.</dd>


<dt>mu</dt>
<dd>the mean parameter. It must lie in (0, 1).</dd>


<dt>phi</dt>
<dd>the precision parameter. It must be a positive real value.</dd>


<dt>p</dt>
<dd>the mixing weight. It must lie in (0, 1).</dd>


<dt>k</dt>
<dd>the extent of the variance inflation. It must lie in (0, 1).</dd>

</dl>

rVIB: Random generation from the variance-inflated beta distribution

Description

Usage

Value

Arguments

References

Examples