Your model is singular. Varying m and log(l) have the same
effect: log(ir) = log(k) + m * log(l) * ox
Also with plinear you don't specify the linear coefficients but
rather an X matrix whose coefficients represent them:
If we use this model instead:
ir = k * exp(m * ox)
Then:
> mod0 <- lm(log(
I'm trying to fit a function y=k*l^(m*x) to some data points, with reasonable
starting value estimates (I think). I keep getting "singular matrix 'a' in
solve".
This is the code:
ox <- c(-600,-300,-200,1,100,200)
ir <- c(1,2.5,4,9,14,20)
model <- nls(ir ~ k*l^(m*ox),start=list(k=10,l=3,m=0.004
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