stoppingcriterion

Different options for the stopping criterion

Functionality to perform adaptive multi-wave sampling for efficient chart validation. Code allows one to define strata, adaptively sample using several types of confidence bounds for the quantity of interest (Lai's confidence bands, Bayesian credible intervals, normal confidence intervals), and sampling strategies (random sampling, stratified random sampling, Neyman's sampling, see Neyman (1934) <doi:10.2307/2342192> and Neyman (1938) <doi:10.1080/01621459.1938.10503378>).

Georg Hahn

chartreview

Adaptive Multi-Wave Sampling for Efficient Chart Validation

Sebastian Schneeweiss

Shirley Wang

stoppingcriterion function

<dl><dt>ci</dt>
<dd>Confidence interval as tuple vector.</dd>
<dt>stopCI</dt>
<dd>Either a confidence interval for stoppingoption=1 and stoppingoption=2, or a scalar for stoppingoption=3.</dd>
<dt>stoppingoption</dt>
<dd>Option to determine if the stopping criterion is satisfied (1 for confidence interval included in stopCI, 2 for upper bound below or lower bound above stopCI, 3 for length restriction on confidence interval).</dd></dl>

Arguments

Different options for the stopping criterion — stoppingcriterion

<dl>

<dt>ci</dt>
<dd>Confidence interval as tuple vector.</dd>


<dt>stopCI</dt>
<dd>Either a confidence interval for stoppingoption=1 and stoppingoption=2, or a scalar for stoppingoption=3.</dd>


<dt>stoppingoption</dt>
<dd>Option to determine if the stopping criterion is satisfied (1 for confidence interval included in stopCI, 2 for upper bound below or lower bound above stopCI, 3 for length restriction on confidence interval).</dd>

</dl>

stoppingcriterion: Different options for the stopping criterion

Description

Usage

Value

Arguments

References

Examples