Dear all I am a bit new to R so please keep your swords sheathed! I would simply like to bootstrap a covariance matrix from a multivariate gaussian density. At face value that seemed like a very straightforward problem to solve but I somehow could not get the boot package to work and did not really understand the documentation so I tried to do the bootstrap manually. Hence:
x<-rmvnorm(n = 5, mean, diag(1,length(mean))) Var<-function(a) var(a) Var(x) sample<-matrix(sample(x,replace=T),ncol=length(mean))#single BS sample Var(sample)# sqr matrix of length(mean) #generate 1000 bootstrap samples boot <- array(NA, c(1000, 3, 3)) #assign the var for bootstrap sample i as the ith element in the vector boot, using a for loop for (i in 1:1000) boot[i,,] <- Var(sample) mean(boot) For output I expect to see a 3x3 covariance matrix but i am getting a single scalar value. So can some person(s) do either (or all) of the following: - point out how I can get the intended result from the above code - point out how the boot function can be used to to solve this problem - point me to further documentation for the boot function p.s: rmvnorm is from the mvtnorm package. Thanks in advance! -- View this message in context: http://r.789695.n4.nabble.com/Bootstrapping-a-covariance-matrix-tp3788553p3788553.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
