dbetabinom_cts

In some cases we may not have integer W and M's. In these cases,
we can still use corncob to estimate parameters, but we need to think of them as
no longer coming from the specific beta binomial parametric model,
and instead from an estimating equations framework.

Statistical modeling for correlated count data using the beta-binomial distribution, described in Martin et al. (2020) <doi:10.1214/19-AOAS1283>. It allows for both mean and overdispersion covariates.

Amy D Willis

corncob

Count Regression for Correlated Observations with the
Beta-Binomial

Bryan D Martin

Daniela Witten

Sarah Teichman

Thomas W Yee

Xiangjie Xue

dbetabinom_cts function

<dl><dt>x</dt>
<dd>the value at which defined the density</dd>
<dt>size</dt>
<dd>number of trials</dd>
<dt>prob</dt>
<dd>the probability of success</dd>
<dt>rho</dt>
<dd>the correlation parameter</dd>
<dt>log</dt>
<dd>if TRUE, log-densities p are given</dd></dl>

Arguments

Thomas W Yee
Xiangjie Xue
Amy D Willis

Author

Densities of beta binomial distributions, permitting non integer x and size — dbetabinom_cts

<dl>

<dt>x</dt>
<dd>the value at which defined the density</dd>


<dt>size</dt>
<dd>number of trials</dd>


<dt>prob</dt>
<dd>the probability of success</dd>


<dt>rho</dt>
<dd>the correlation parameter</dd>


<dt>log</dt>
<dd>if TRUE, log-densities p are given</dd>

</dl>

dbetabinom_cts: Densities of beta binomial distributions, permitting non integer x and size

Description

Usage

Arguments

Author