print.nDesign

print.sDesign

Print function for results of functions <code>nDesign</code>, <code>nDesign</code>.

 print

print.bgtDesign

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

print.bgtDesign function

<dl> <dt>x</dt>
<dd>An object of class <kbd>"nDesign"</kbd> or <kbd>"sDesign"</kbd></dd> <dt>...</dt>
<dd>currently only <code>digits</code> is passed to <code>signif</code> for appropriate rounding</dd></dl>

Arguments

Print Functions for nDesign and sDesign — print.bgtDesign

<dl>

 <dt>x</dt>
<dd>An object of class <kbd>"nDesign"</kbd> or <kbd>"sDesign"</kbd></dd>

 <dt>...</dt>
<dd>currently only <code>digits</code> is passed to <code>signif</code> for appropriate rounding</dd>

</dl>

print.bgtDesign: Print Functions for nDesign and sDesign

Description

Usage

Arguments