Check the accuracy of the parameter estimates of cumulative link
models. The number of correct decimals and number of significant
digits is given for the maximum likelihood estimates of the parameters
in a cumulative link model fitted with clm
.
convergence(object, ...)# S3 method for clm
convergence(object, digits = max(3, getOption("digits") - 3),
tol = sqrt(.Machine$double.eps), ...)
Convergence information. In particular a table where the Error
column gives the numerical error in the parameter estimates. These
numbers express how far the parameter estimates in the fitted model
are from the true maximum likelihood estimates for this
model. The Cor.Dec
gives the number of correct decimals with
which the the parameters are determined and the Sig.Dig
gives
the number of significant digits with which the parameters are
determined.
The number denoted logLik.error
is the error in the value of
log-likelihood in the fitted model at the parameter values of that
fit. An accurate determination of the log-likelihood is essential for
accurate likelihood ratio tests in model comparison.
for the clm
method an object of class
"clm"
, i.e., the result of a call to clm
.
the number of digits in the printed table.
numerical tolerence to judge if the Hessian is positive definite from its smallest eigenvalue.
arguments to a from methods. Not used by the clm
method.
Rune Haubo B Christensen
The number of correct decimals is defined as...
The number of significant digits is defined as ...
The number of correct decimals and the number of significant digits are determined from the numerical errors in the parameter estimates. The numerical errors are determined from the Method Independent Error Theorem (Elden et al, 2004) and is based on the Newton step evaluated at convergence.
Elden, L., Wittmeyer-Koch, L. and Nielsen, H. B. (2004) Introduction to Numerical Computation --- analysis and Matlab illustrations. Studentliteratur.
## Simple model:
fm1 <- clm(rating ~ contact + temp, data=wine)
summary(fm1)
convergence(fm1)
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