Performs Parametric Bootstrap for Standard Error Approximation
Performs a parametric bootstrap by producing B bootstrap samples for the parameters in the specified mixture model.
boot.se(em.fit, B = 100, arbmean = TRUE, arbvar = TRUE,
N = NULL, ...)em.fit |
An object of class |
B |
The number of bootstrap samples to produce. The default is 100, but ideally, values of 1000 or more would be more acceptable. |
arbmean |
If FALSE, then a scale mixture analysis can be performed for |
arbvar |
If FALSE, then a location mixture analysis can be performed for |
N |
An n-vector of number of trials for the logistic regression type |
... |
Additional arguments passed to the various EM algorithms for the mixture of interest. |
boot.se returns a list with the bootstrap samples and standard errors for the mixture of interest.
McLachlan, G. J. and Peel, D. (2000) Finite Mixture Models, John Wiley \& Sons, Inc.
## Bootstrapping standard errors for a regression mixture case. data(NOdata) attach(NOdata) set.seed(100) em.out <- regmixEM(Equivalence, NO, arbvar = FALSE) out.bs <- boot.se(em.out, B = 10, arbvar = FALSE) out.bs
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