Hi, this question may be off topic: the unbiased estimator of the variance of the errors in a linear regression moedel with p coefficients is: sigma2=sum((y-yi)^2)/(length(y)-p-1) But what if i estimate transformations of the dependent an independent variables (e.g. Box-Cox) too? May I calculate the variance using sigma2=sum((y-yi)^2)/(length(y)-2*p-1) or should I use the first formula then? Thank you, Tim ================================================= Where Do You Want To Go Tomorrow? http://www.GoPenguin.com GoPenguin Network Inc. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
variance of a linear model
1 message · Tim Hannig