findA

Computes the first parameter value for a given KL
divergence and UMP test.

When using pooled p-values to adjust for multiple testing, there is an inherent balance that must be struck between rejection based on weak evidence spread among many tests and strong evidence in a few, explored in Salahub and Olford (2023) <arXiv:2310.16600>. This package provides functionality to compute marginal and central rejection levels and the centrality quotient for p-value pooling functions and provides implementations of the chi-squared quantile pooled p-value (described in Salahub and Oldford (2023)) and a proposal from Heard and Rubin-Delanchy (2018) <doi:10.1093/biomet/asx076> to control the quotient's value.

Chris Salahub

PoolBal

Balancing Central and Marginal Rejection of Pooled p-Values

findA function

<dl><dt>w</dt>
<dd>UMP parameter between 0 and 1</dd>
<dt>logd</dt>
<dd>numeric value, the log KL divergence</dd>
<dt>...</dt>
<dd>additional arguments to uniroot</dd></dl>

Arguments

Author

Estimate parameter for a given beta KL divergence and UMP
test — findA

<dl>

<dt>w</dt>
<dd>UMP parameter between 0 and 1</dd>


<dt>logd</dt>
<dd>numeric value, the log KL divergence</dd>


<dt>...</dt>
<dd>additional arguments to uniroot</dd>

</dl>

findA: Estimate parameter for a given beta KL divergence and UMP test

Description

Usage

Value

Arguments

Author

Details

Examples