Thanks for the tip. I actually had to learn a bit of matrix multiplication and ended up calculating the RMSE this way.
scores_lr <- t(coeffs_alldata) %*% t(df_train) rmseTrain <- (mean(((scores_lr)- trainY)^2))^0.5 full script and results here if you are interested. http://ausdm09.freeforums.org/post34.html#p34 tdm wrote: > > I have build a model but want to then manipulate the coefficients in some > way. > > I can extract the coefficients and do the changes I need, but how do I > then put these new coefficients back in the model so I can use the predict > function? > > my_model <- lm(x ~ . , data=my_data) > my_scores <- predict(my_model, my_data) > > my_coeffs <- coef(my_model) > > ## here we manipulate my_coeffs > ## and then want to set the my_model > ## coefficients to the new values so we > ## predict using the new values > > my_model.coefs <- my_coeffs ?? how is this done? > > ?? so that this will work with the new coefficients > my_scores_new <- predict(my_model, my_data) > > Any code snippets would be appreciated very much. > > -- View this message in context: http://www.nabble.com/modifying-model-coefficients-tp25952879p25964671.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org 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.
