Off topic I think. This is a statistical question, not an R programming question.
There are certainly many internet tutorials on this -- e.g. "bias and variance in linear models" as a search term. You might also consider search terms like "shrinkage estimators", "penalized regression". "regularization", "ridge regression,"and the like if you care to go deeper. Cheers, Bert On Wed, Apr 26, 2023 at 1:32 PM varin sacha via R-help <r-help@r-project.org> wrote: > Dear R-experts, > > Here below a toy example to calculate the MSE (mean squared error). > > Starting from this equation : MSE = bias^2 + variance + irreducible error > > I am trying to get the bias and the variance in addition to the MSE. How > to get them both? > > Many thanks for your help. > > > ######################################################### > #Data > y=c(23,34,54,34,23,34,43,45,56,65,45,42,32,35,37,41,54,56,53,45) > x1=c(2,4,3,5,4,6,4,3,2,1,2,3,4,3,5,6,7,6,4,3) > x2=c(11,12,13,21,14,13,15,17,18,16,21,21,23,19,11,10,19,17,16,11) > x3=c(45,46,34,24,47,48,50,40,41,39,37,34,50,56,53,51,37,48,49,53) > > #Fit the model > model=lm(y~x1+x2+x3) > > #Calculate MSE > model_summ=summary(model) > mean(model_summ$residuals^2) > ########################################################### > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > 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. > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
