Dear List, Why do commonly used estimator functions (such as lm(), glm(), etc.) not allow negative case weights? I suspect that there is a good reason for this. Yet, I can see reasonable cases when one wants to use negative case weights.
Take lm() for example: ### n <- 20 Y <- rnorm(n) X <- cbind(rep(1,n),runif(n),rnorm(n)) Weights <- rnorm(n) # Includes Pos and Neg Weights Weights # Now do Weighted LS and get beta coeffs: b <- solve(t(X)%*%diag(Weights)%*%X) %*% t(X) %*% diag(Weights)%*%Y b # This seems like a valid model, but when I try lm(Y ~ X[,2:3],weights=Weights) # I get: "missing or negative weights not allowed" ### What is the rationale for not allowing negative weights? I ask this, because I am currently trying to implement a (two stage) estimator into R that involves negative case weights. Weights are generated in the first stage, so it would be nice if I could use canned functions such as lm(,weights=Weights) in the second stage. Thank you for your help. Best, Jens ______________________________________________ R-help@stat.math.ethz.ch 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.