getSegmentProb

<code>getSegmentProb</code> is an internal function for
converting a theta distribution to segment-wise classification probabilities
This is used for <code>BIGM-BAYESIAN</code> exposure control.

internal

Uses the optimal test design approach by Birnbaum (1968, ISBN:9781593119348) and
van der Linden (2018) <doi:10.1201/9781315117430> to construct fixed, adaptive, and parallel tests.
Supports the following mixed-integer programming (MIP) solver packages: 'Rsymphony',
'highs', 'gurobi', 'lpSolve', and 'Rglpk'. The 'gurobi' package is not available from CRAN; see <https://www.gurobi.com/downloads/>.

Seung W. Choi

TestDesign

Optimal Test Design Approach to Fixed and Adaptive Test
Construction

Sangdon Lim

getSegmentProb function

<dl><dt>posterior_sample</dt>
<dd>a vector containing values in a Markov chain.</dd>
<dt>simulation_constants</dt>
<dd>a named list containing simulation constants.</dd></dl>

Arguments

(Internal) Convert a theta distribution to segment-wise classification probabilities — getSegmentProb

<dl>

<dt>posterior_sample</dt>
<dd>a vector containing values in a Markov chain.</dd>


<dt>simulation_constants</dt>
<dd>a named list containing simulation constants.</dd>

</dl>

getSegmentProb: (Internal) Convert a theta distribution to segment-wise classification probabilities

Description

Usage

Value

Arguments