Re: [R] Error in lm() with very small (close to zero) regressor

I found a fix to my problem using the fastLm() from package RcppEigen, using the Jacobi singular value decomposition (SVD) (method 4) or a method based on the eigenvalue-eigenvector decomposition of X'X - method 5 of the fastLm function install.packages("RcppEigen") library(RcppEigen) n_obs <-

Re: [R] Error in lm() with very small (close to zero) regressor

RiGui business.uzh.ch> writes: > [snip] > I am terribly sorry for the code not being reproducible, is the > first time I am posting here, I run the code several times before I > posted, but...I forgot about the library used. Thanks for updating. > To answer to your qu

Re: [R] Error in lm() with very small (close to zero) regressor

Thank you for your replies! I am terribly sorry for the code not being reproducible, is the first time I am posting here, I run the code several times before I posted, but...I forgot about the library used. To answer to your questions: How do you know this answer is "correct"? What I am doing

[R] Error in lm() with very small (close to zero) regressor

Hello everybody, I have encountered the following problem with lm(): When running lm() with a regressor close to zero - of the order e-10, the value of the estimate is of huge absolute value , of order millions. However, if I write the formula of the OLS estimator, in matrix notation: pseudoinv