I'm using netlm() from the sna package to regress one variable on another in order to get fitted and residual values. I set mode argument inside netlm() to undirected "graph" with 10 times QAP. Then I checked the output.
The output contains 12,880 fitted and residual values and, given that the dimension of my data is 161 * 161, this means that they represent the fitted/residual values for the lower (or upper) diagonal matrix data minus main diagonal values ((161*161)/2 - 161 = 12880). If I want to generate a new matrix of the same dimension as my data and filled both upper and lower diagonals with fitted values, how I can make sure that those values will actually be filled into their corresponding cells?
It will be really appreciated if someone could shed some light on this. I provide my code at below for your reference.
library(sna)
x <- readRDS(url("https://www.dropbox.com/s/v1kz95luew28o7u/xki_ratio2019.rds?dl=1"))
y <- readRDS(url("https://www.dropbox.com/s/yc7md37x6albxog/xki_lag.rds?dl=1"))
model.nl <- netlm(y[[1]], list(x), diag = FALSE, mode = "graph", nullhyp=c("qapx"), reps = 100)
dim(x)
161 161
length(model.nl$residuals)
12880Something like
resid <- matrix(NA, 161, 161)
resid[upper.tri(resid)] <- model.nl$residuals
Not sure whether you want upper.tri or lower.tri off the top of my head, and you might need to transpose