Hi everyone! In a package I'm developing, I have created a custom function to get jackknife standard errors for the parameters of a gnm model (which is essentially the same as a glm model for this issue). I'd like to add support for bootstrap using package boot, but I couldn't find how to proceed.
The problem is, my data is a table object. Thus, I don't have one individual per line: when the object is converted to a data frame, one row represents one cell, or one combination of factor levels. I cannot pass this to boot() as the "data" argument and use "indices" from my custom statistic() function, since I would drop cells, not individual observations. A very inefficient solution would be to create a data frame with one row per observation, by replicating each cell using its frequencies. That's really a brute force solution, though. ;-) The other way would be generate importance weights based on observed frequencies, and to multiply the original data by the weights at each iteration, but I'm not sure that's correct. Thoughts? Thanks for your help! ______________________________________________ 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.
