I used lsfit instead of lm since I have a huge Y data-set (X being constant for all Y).
Since I require the t-values for all coefficients: which would be the fastest way to compute them, eg for the example:
## using lsfit with a matrix response:
t.length <- 5
d.dim <- c(t.length,7,8,9) # dimesions: time, x, y, z
Y <- array( rep(1:t.length, prod(d.dim)) + rnorm(prod(d.dim), 0, 0.1), d.dim)
X <- cbind(c(1,3,2,4,5), c(1,1,1,5,5))
date()
rsq <-lsfit(X, array(c(Y), dim = c(t.length, prod(d.dim[2:4]))))$coef[2,] #coef for first non-const pred
names(rsq) <- prod(d.dim[2:4])
rsq <- array(rsq, dim = d.dim[2:4])
date()
what would be the best way to get the t-value for all coef, not only (as above illustrated for the beta value) for one predefined coef?
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many thanks christoph
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