I fitted a mixture denstiy of two gaussians two my data. I now want to calculated the standard errors of the estimates via the boot.se command of the mixtools package. My question is now, if the output is correct? It seems a bit odd to me, so is this correct what I am doing and can I rely on the values?
My data: http://s000.tinyupload.com/?file_id=09285782882980618119 My code: normalmix<-normalmixEM(dat,k=2,lambda=c(0.99024,(1-0.99024)),fast=FALSE,maxit=10000,epsilon = 1e-16,maxrestarts=1000) normalmix$loglik normalmix$lambda se<-boot.se(normalmix,B=1000) se$lambda.se se$mu.se se$sigma.se final results: lambdahat = 0.990238663 mu1hat= -0.00115 mu2hat= 0.040176949 sigma1hat= 0.012220305 sigma2hat= 0.003247102 My problem now is - and thats why I feel uncomfortable about relying on the values - that the output of boot.se(normalmix) varies quite strong. So without changing the code and rerun it (with the same normalmix, so normalmix is not rerun again) I get different estimates of the standard error. I increased the default value for B from 100 to 1000. In the manual there is nothing said about any other randomness. So where does it come from? What should I do now? [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
