flexmix object perform parametric or empirical bootstrap.boot(object, ...)
## S3 method for class 'flexmix':
boot(object, R, sim = c("ordinary", "empirical", "parametric"),
initialize_solution = FALSE, keep_weights = FALSE,
keep_groups = TRUE, verbose = 0, control,
k, model = FALSE, ...)
LR_test(object, ...)
## S3 method for class 'flexmix':
LR_test(object, R, alternative = c("greater", "less"), control, ...)flexmix."ordinary" (the default),
"parametric", or "empirical".TRUE the EM algorithm is
initialized in the given solution.TRUE the weights are kept.TRUE the groups are kept.verbose iterations. If 0,
no output is generated during the bootstrap replications.FLXcontrol or a named list.
If missing the control of the fitted object is taken.object are taken."greater" (default) or
"less" indicating if the alternative hypothesis is that the
mixture has one more component or one less.TRUE the model and the weights slot for
each sample are stored and returned.boot returns an object of class FLXboot which
contains the fitted parameters, the fitted priors, the log
likelihoods, the number of components of the fitted mixtures and the
information if the EM algorithm has converged. LR_test returns an object of class htest containing the
number of valid bootstrap replicates, the p-value, the - twice log
likelihood ratio test statistics for the original data and the
bootstrap replicates.
data("NPreg", package = "flexmix")
fitted <- initFlexmix(yn ~ x + I(x^2) | id2, data = NPreg, k = 2)
lrtest <- LR_test(fitted, alternative = "greater", R = 20,
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