gt.control

Auxiliary function to control fitting parameters of EM algorithm used internally in <code>gtreg.mp</code> and <code>EM.mp</code> or <code>gtreg</code>, <code>EM</code>, and <code>EM.ret</code>.

misc

Methods for estimation and hypothesis testing of proportions
in group testing designs: methods for estimating a proportion in a single
population (assuming sensitivity and specificity equal to 1 in designs
with equal group sizes), as well as hypothesis tests and
functions for experimental design for this situation. For
estimating one proportion or the difference of proportions, a
number of confidence interval methods are included, which can
deal with various different pool sizes. Further, regression
methods are implemented for simple pooling and matrix pooling
designs.
Methods for identification of positive items in group
testing designs: Optimal testing configurations can be found
for hierarchical and array-based algorithms. Operating
characteristics can be calculated for testing configurations
across a wide variety of situations.

Frank Schaarschmidt

binGroup

Evaluation and Experimental Design for Binomial Group Testing

Boan Zhang

Christopher Bilder

Brad Biggerstaff

Brianna Hitt

gt.control function

<dl> <dt>tol</dt>
<dd>convergence criterion</dd> <dt>n.gibbs</dt>
<dd>the Gibbs sample size to be used in each E step for the EM algorithm (default is 1000), for matrix pooling</dd> <dt>n.burnin</dt>
<dd>the number of samples in the burn-in period (default is 20), for matrix pooling</dd> <dt>maxit</dt>
<dd>maximal number of iterations in the EM algorithm</dd> <dt>trace</dt>
<dd>logical indicating if output should be printed for each iteration, defaults to <kbd>FALSE</kbd></dd> <dt>time</dt>
<dd>logical indicating if the length of time for the model fitting should be printed, defaults to <kbd>TRUE</kbd></dd></dl>

Arguments

Auxiliary for Controlling Group Testing Regression — gt.control

<dl>

 <dt>tol</dt>
<dd>convergence criterion</dd>

 <dt>n.gibbs</dt>
<dd>the Gibbs sample size to be used in each E step for the EM algorithm (default is 1000), for matrix pooling</dd>

 <dt>n.burnin</dt>
<dd>the number of samples in the burn-in period (default is 20), for matrix pooling</dd>

 <dt>maxit</dt>
<dd>maximal number of iterations in the EM algorithm</dd>

 <dt>trace</dt>
<dd>logical indicating if output should be printed for each iteration, defaults to <kbd>FALSE</kbd></dd>

 <dt>time</dt>
<dd>logical indicating if the length of time for the model fitting should be printed, defaults to <kbd>TRUE</kbd></dd>

</dl>

gt.control: Auxiliary for Controlling Group Testing Regression

Description

Usage

Value

Arguments

Examples