applyThin

<code>applyThin</code> is an internal function for
thinning a Markov chain. Burn-in is also applied.

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

applyThin function

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

Arguments

(Internal) Thin a MCMC chain — applyThin

<dl>

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


<dt>bayesian_constants</dt>
<dd>a named list containing Bayesian constants.</dd>

</dl>

applyThin: (Internal) Thin a MCMC chain

Description

Usage

Value

Arguments