Computes simultaneous confidence intervals for multinomial proportions
using the Goodman (1965) method. The function calculates lower and upper
confidence limits for each category, adjusts them to remain within the
[0, 1] range, and computes the overall interval volume (the product of
interval widths).

Several authors have proposed methods for constructing simultaneous confidence intervals for multinomial proportions. The package implements seven classical approaches—Wilson, Quesenberry and Hurst, Goodman, Wald (with and without continuity correction), Fitzpatrick and Scott, and Sison and Glaz—along with Bayesian methods based on Dirichlet models. Both equal and unequal Dirichlet priors are supported, providing a broad framework for inference, data analysis, and sensitivity evaluation.

originally by Subbiah M  packaged by Sumathi R

CoinMinD

Simultaneous Confidence Intervals for Multinomial Proportions

Subbiah M

GM function

<dl><dt>inpmat</dt>
<dd>Integer vector of observed cell counts corresponding to
a categorical dataset. Must contain non-negative values.</dd>
<dt>alpha</dt>
<dd>Desired statistical significance level</dd></dl>

Arguments

Author

GM: Goodman Method for Simultaneous Confidence Intervals — GM

<dl>

<dt>inpmat</dt>
<dd>Integer vector of observed cell counts corresponding to
a categorical dataset. Must contain non-negative values.</dd>


<dt>alpha</dt>
<dd>Desired statistical significance level</dd>

</dl>

GM: GM: Goodman Method for Simultaneous Confidence Intervals

Description

Usage

Value

Arguments

Author

Details

References

See Also

Examples