Dennis: thank you so much! I got it now and it works just perfectly. Thanks a lot to the others too! Anna
2011/3/21 Dennis Murphy <djmu...@gmail.com>: > Hi: > > To amplify Ista's and David's comments: > > (1) You should not be inputting separate vectors into lm(), especially if > you intend to do prediction. They should be combined into a data frame > instead. This is not a requirement, but it's a much safer strategy for > modeling in R. > (2) Your covariate st does not have a linear component. It should, > particularly if this is an empirical model rather than a theoretical one. > (3) You should be using poly(var, 2) to create orthogonal columns in the > model matrix for the variables that are to contain quadratic terms. > (4) The newdata = argument of predict.lm() [whose help page you should read > carefully] requires a data frame with columns having precisely the same > variable names as exist in the RHS of the model formula in lm(). > > Example: > dd <- data.frame(y = rnorm(50), x1 = rnorm(50), x2 = runif(50, -2, 2), x3 = > rpois(50, 10)) > > # fit yhat = b0 + b1 * x1 + b2 * x1^2 + b3 * x2 + b4 * x3 + b5 * x3^2 > mod <- lm(y ~ poly(x1, 2) + x2 + poly(x3, 2), data = dd) > > # Note that the names of the variables in newd are the same as those on the > RHS of the formula in mod > newd <- data.frame(x1 = rnorm(5), x2 = runif(5, -2, 2), x3 = rpois(5, > 10)) # new data points > # Append predictions to newd > cbind(newd, predict(mod, newdata = newd)) # predictions at new > data points > > # To just get predictions at the observed points, all you need is > predict(mod) > > HTH, > Dennis > > On Sun, Mar 20, 2011 at 11:54 AM, Anna Lee <ana-...@web.de> wrote: >> >> Hey List, >> >> I did a multiple regression and my final model looks as follows: >> >> model9<-lm(calP ~ nsP + I(st^2) + distPr + I(distPr^2)) >> >> Now I tried to predict the values for calP from this model using the >> following function: >> >> xv<-seq(0,89,by=1) >> yv<-predict(model9,list(distPr=xv,st=xv,nsP=xv)) >> >> The predicted values are however strange. Now I do not know weather >> just the model does not fit the data (actually all coefficiets are >> significant and the plot(model) shows a good shape) or wether I did >> something wrong with my prediction command. Does anyone have an >> idea??? >> >> -- >> >> >> Thanks a lot, Anna >> >> ______________________________________________ >> 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. > > -- Der Inhalt dieser E-Mail ist vertraulich. Sollte Ihnen die E-Mail irrtümlich zugesandt worden sein, bitte ich Sie, mich unverzüglich zu benachrichtigen und die E-Mail zu löschen. This e-mail is confidential. If you have received it in error, please notify me immediately and delete it from your system. ______________________________________________ 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.
