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Starting Values and Fine Tuning of the MCEM algorithm
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.. r-package:: manifestos
.. r-name:: latpos_tunefit
latpos.control
latpos.start
Description
===========
Function ``latpos.start`` is used to construct "good" starting values,
while function ``latpos.control`` provides settings for the numerical
aspects of the MCEM algorithm, with reasonable defaults.
Usage
=====
.. code-block:: r
latpos.start(resp,latent.dims,manifest,start,
unfold.method,restrictions=standard.restrictions,
maxiter,...)
latpos.control(maxiter=200,initial.size=101,
Lambda.alpha=.05,
Lambda.eps=1e-7,
diff.logLik.eps=1e-7,
abs.diff.psi.eps=0,
rel.diff.psi.eps=0,
max.size=Inf,
min.final.size=1000,
force.increase=TRUE,
Q.linesearch=TRUE,
...)
Arguments
=========
``resp``
an internal representation of the observed data.
``latent.dims``
a character vector with the names of the axes of the latent space.
``manifest``
a character vector with the names of the observed variables, i.e.
emphasis counts of policy objectives.
``start``
an optional list with starting values for the model parameters
``unfold.method``
the unfolding method to be used to generate reasonable starting values.
``restrictions``
an object representing restrictions on the model parameters, see
``restrictor``.
``maxiter``
the maximum number of iterations to use, in ``latpos.start`` to get
initial values for the posterior modes, in ``latpos.control`` to set
the maximum number of MCEM iterations.
``initial.size``
a positive number, the simulation sample size to use in the first MCEM
iteration.
``Lambda.alpha``
a "significance level" for the increase of the Q-function. If the
increase is not "statistically significant" at this level, the sample
size is automatically increased.
``Lambda.eps``
a non-negative number as convergence critierion. If the increase of
the Q-function is smaller than this value, convergence of the MCEM is
declared.
``diff.logLik.eps``
a non-negative number as convergence critierion. If the increase of
the marginal log-likelihood is smaller than this value, convergence of
the MCEM is declared.
``abs.diff.psi.eps``
a non-negative number as an alternative convergence critierion. if the
absolute change of the model parameters is smaller than this value,
convergence of the MCEM is declared.
``rel.diff.psi.eps``
a non-negative number as an alternative convergence critierion. if the
absolute change of the model parameters is smaller than this value,
convergence of the MCEM is declared.
``max.size``
a positive number, the maximum simulation sample size to be used.
``min.final.size``
a positive number, the minimal simulation sample size to be used in the
final iterations of the MCEM algorithm.
``force.increase``
logical; if TRUE and the likelihood or the Q-function cannot be
increased then conduct a line search for the optimal step size.
``Q.linesearch``
logical; if TRUE, force.increase==TRUE and the likelihood or the
Q-function cannot be increased then conduct a line search for the
optimal step size; if FALSE, but force.increase==TRUE and the
likelihood or the Q-function cannot be increased then step back to the
values of the previous iteration.
``...``
other arguments, ignored.