## S3 method for class 'flexmix':
refit(object, newdata, method = c("optim",
"mstep"), ...)
## S3 method for class 'FLXRoptim':
summary(object, model = 1, which = c("model",
"concomitant"), ...)
## S3 method for class 'FLXRmstep':
summary(object, model = 1, which = c("model",
"concomitant"), ...)## S3 method for class 'FLXRoptim,missing':
plot(x, y, model = 1, which = c("model", "concomitant"),
bycluster=TRUE, alpha=0.05, components, labels=NULL,
significance = FALSE, xlab = NULL, ylab = NULL, ci = TRUE,
scales = list(), as.table = TRUE, horizontal = TRUE, ...)
"flexmix"optim or if the posteriors are
assumed as given and an M-step is performed."FLXRoptim"xyplot.xyplot.xyplot.FLXR is returned. For the
method using optim the object has class FLXRoptim and
for the M-step method it has class FLXRmstep. Both classes give
similar results for their summary methods.
Objects of class FLXRoptim have their own plot method.
Lapply can be used to further analyse the refitted component
specific models of objects of class FLXRmstep.method = "mstep" the standard deviations are determined
separately for each of the components using the a-posteriori
probabilities as weights without accounting for the fact that the
components have been simultaneously estimated. The derived standard
deviations are hence approximative and should only be used in an
exploratory way, as they are underestimating the uncertainty given
that the missing information of the component memberships are replaced
by the expected values. The newdata argument can only be specified for refitting
FLXMRglm components using method = "mstep". A variant of
glm for weighted ML estimation is used for fitting the
components and full glm objects are returned. Please note that
in this case the data and the model frame are stored for each
component which can significantly increase the object size.
refit method for FLXMRglm models in
combination with the summary method can be
used to obtain the usual tests for significance of coefficients. Note
that the tests are valid only if flexmix returned the maximum
likelihood estimator of the parameters. If refit is used with
method = "mstep" for these component specific models the
returned object contains a glm object for each component where
the elements model which is the model frame and data
which contains the original dataset are missing.data("NPreg", package = "flexmix")
ex1 <- flexmix(yn~x+I(x^2), data=NPreg, k=2)
ex1r <- refit(ex1)
## in one component all coefficients should be highly significant,
## in the other component only the linear term
summary(ex1r)Run the code above in your browser using DataLab