hd.diffbetas

Computes the highest density interval for the difference of two beta distributions.

Computation of the minimum sample size using the Average
Coverage Criterion or the Average Length Criterion for estimating
binomial proportions using beta prior distributions. For more details
see Costa (2025) <DOI:10.1007/978-3-031-72215-8_14>.

Eliardo Costa

bssbinom

Bayesian Sample Size for Binomial Proportions

hd.diffbetas function

<dl><dt>c1</dt>
<dd>First parameter of the beta distribution of the first proportion.</dd>
<dt>d1</dt>
<dd>Second parameter of the beta distribution of the first proportion.</dd>
<dt>c2</dt>
<dd>First parameter of the beta distribution of the second proportion.</dd>
<dt>d2</dt>
<dd>Second parameter of the beta distribution of the second proportion.</dd>
<dt>rho</dt>
<dd>A number in (0, 1) representing the fixed probability for the HD interval.</dd>
<dt>len</dt>
<dd>A positive real number representing the fixed length for the HD interval.</dd>
<dt>N</dt>
<dd>Number of replicates used in the simulation. Default is 1000.</dd></dl>

Arguments

HD interval for the difference of two beta distributions — hd.diffbetas

<dl>

<dt>c1</dt>
<dd>First parameter of the beta distribution of the first proportion.</dd>


<dt>d1</dt>
<dd>Second parameter of the beta distribution of the first proportion.</dd>


<dt>c2</dt>
<dd>First parameter of the beta distribution of the second proportion.</dd>


<dt>d2</dt>
<dd>Second parameter of the beta distribution of the second proportion.</dd>


<dt>rho</dt>
<dd>A number in (0, 1) representing the fixed probability for the HD interval.</dd>


<dt>len</dt>
<dd>A positive real number representing the fixed length for the HD interval.</dd>


<dt>N</dt>
<dd>Number of replicates used in the simulation. Default is 1000.</dd>

</dl>

hd.diffbetas: HD interval for the difference of two beta distributions

Description

Usage

Value

Arguments

References

Examples