statistics-bootstrap

I want to use the new bootMer() feature of the new lme4 package (the developer version currently). I am new to R and don't know which function should I write for its FUN argument. It says it needs a numerical vector, but I have no idea what that function will perform. So I have a mixed-model formula which is cast to the bootMer(), and have a number of replicates. So I don't know what that external function does? Is it supposed to be a template for bootstrapping methods? Aren't bootstrapping methods already implemented in he bootMer? So why they need an external "statistic of interest"? And

I have a matrix A , and I would like to draw samples from each column of A and construct new matrices. For example: A = matrix(seq(1,9),3,3) so to get the 1st bootstrap matrix, I would sample with replacement (3 times) from the first column of A , i.e. 1,2,3, sample with replacement (3 times) from the second column of A , i.e. 4,5,6, and sample with replacement (3 times) from the third column of A , i.e. 7,8,9. After that, I re-construct the 1st bootstrap matrix B1 by combining the three bootstrap vectors. I will repeat this procedure for B=199 times, so that bootstrap matrices B1,...,B199

I'm most grateful for your time to read this. I have a uber size 30GB file of 6 million records and 3000 (mostly categorical data) columns in csv format. I want to bootstrap subsamples for multinomial regression, but it's proving difficult even with my 64GB RAM in my machine and twice that swap file , the process becomes super slow and halts. I'm thinking about generating subsample indicies in R and feeding them into a system command using sed or awk, but don't know how to do this. If someone knew of a clean way to do this using just R commands, I would be really grateful. One problem is that

I'm trying to efficiently implement a block bootstrap technique to get the distribution of regression coefficients. The main outline is as follows. I have a panel data set, and say firm and year are the indices. For each iteration of the bootstrap, I wish to sample n subjects with replacement. From this sample, I need to construct a new data frame that is an rbind() stack of all the observations for each sampled subject, run the regression, and pull out the coefficients. Repeat for a bunch of iterations, say 100. Each firm can potentially be selected multiple times, so I need to include it