rBetaBin

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

size

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

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

theta

the precision parameter. It is an alternative way to specify the <code>theta</code> parameter. It must be a positive real value.

The function randomly generates values from the beta-binomial 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

rBetaBin 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>size</dt>
<dd>the total number of trials.</dd>
<dt>mu</dt>
<dd>the mean parameter. It must lie in (0, 1).</dd>
<dt>theta</dt>
<dd>the overdispersion parameter. It must lie in (0, 1).</dd>
<dt>phi</dt>
<dd>the precision parameter. It is an alternative way to specify the <code>theta</code> parameter. It must be a positive real value.</dd></dl>

Arguments

Random generator from the beta-binomial distribution — rBetaBin

<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>size</dt>
<dd>the total number of trials.</dd>


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


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


<dt>phi</dt>
<dd>the precision parameter. It is an alternative way to specify the <code>theta</code> parameter. It must be a positive real value.</dd>

</dl>

rBetaBin: Random generator from the beta-binomial distribution

Description

Usage

Value

Arguments

References

Examples