dirichlet.mle

Data frame with \(N\) observations and \(K\) variables
of a Dirichlet distribution

Optional vector of frequency weights

weights

Tolerance number which is added to prevent from logarithms of zero

convcrit

maxit

Convergence acceleration factor. It must be a parameter
between 0 and 1.

oldfac

progress

Maximum likelihood estimation of the parameters of the Dirichlet
distribution

Supplementary functions for item response models aiming
to complement existing R packages. The functionality includes among others
multidimensional compensatory and noncompensatory IRT models
(Reckase, 2009, <doi:10.1007/978-0-387-89976-3>),
MCMC for hierarchical IRT models and testlet models
(Fox, 2010, <doi:10.1007/978-1-4419-0742-4>),
NOHARM (McDonald, 1982, <doi:10.1177/014662168200600402>),
Rasch copula model (Braeken, 2011, <doi:10.1007/s11336-010-9190-4>;
Schroeders, Robitzsch & Schipolowski, 2014, <doi:10.1111/jedm.12054>),
faceted and hierarchical rater models (DeCarlo, Kim & Johnson, 2011,
<doi:10.1111/j.1745-3984.2011.00143.x>),
ordinal IRT model (ISOP; Scheiblechner, 1995, <doi:10.1007/BF02301417>),
DETECT statistic (Stout, Habing, Douglas & Kim, 1996,
<doi:10.1177/014662169602000403>), local structural equation modeling
(LSEM; Hildebrandt, Luedtke, Robitzsch, Sommer & Wilhelm, 2016,
<doi:10.1080/00273171.2016.1142856>).

Alexander Robitzsch

sirt

Supplementary Item Response Theory Models

dirichlet.mle function

<dl> <dt>x</dt>
<dd>Data frame with \(N\) observations and \(K\) variables
of a Dirichlet distribution</dd><dt>weights</dt>
<dd>Optional vector of frequency weights</dd> <dt>eps</dt>
<dd>Tolerance number which is added to prevent from logarithms of zero</dd> <dt>convcrit</dt>
<dd>Convergence criterion</dd> <dt>maxit</dt>
<dd>Maximum number of iterations</dd><dt>oldfac</dt>
<dd>Convergence acceleration factor. It must be a parameter
between 0 and 1.</dd> <dt>progress</dt>
<dd>Display iteration progress?</dd></dl>

Arguments

Maximum Likelihood Estimation of the Dirichlet Distribution — dirichlet.mle

<dl>

 <dt>x</dt>
<dd>Data frame with \(N\) observations and \(K\) variables
of a Dirichlet distribution</dd>

<dt>weights</dt>
<dd>Optional vector of frequency weights</dd>

 <dt>eps</dt>
<dd>Tolerance number which is added to prevent from logarithms of zero</dd>

 <dt>convcrit</dt>
<dd>Convergence criterion</dd>

 <dt>maxit</dt>
<dd>Maximum number of iterations</dd>

<dt>oldfac</dt>
<dd>Convergence acceleration factor. It must be a parameter
between 0 and 1.</dd>

 <dt>progress</dt>
<dd>Display iteration progress?</dd>

</dl>

dirichlet.mle: Maximum Likelihood Estimation of the Dirichlet Distribution

Description

Usage

Value

Arguments

References

See Also