then is the nls function can deal the problem as Guillaume STORCHI mentioned in the last post? [X<-nls(y~x+exp(a*x)*eps, data=,start=list(a=,eps=))] or just can solve the problem as:log(y-x) = a*x + e?
On Fri, 18 Mar 2005 08:56:38 -0500 "Liaw, Andy" <[EMAIL PROTECTED]> wrote: > AFAIK most model fitting techniques will only deal with additive errors, not > multiplicative ones. You might want to try fitting: > > log(y-x) = a*x + e > > which is linear. > > Andy > > > From: Angelo Secchi > > > > Hi, > > is there a way in R to fit a non linear model like > > > > y=x+exp(a*x)*eps > > > > where a is the parameter and eps is the error term? > > Thanks > > Angelo > > > > ______________________________________________ > > 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 > > > > > > > > ______________________________________________ > 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 ______________________________________________ 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
