Dear Eric, Many thanks, I correct your 2 points and now I get another error message (Error in splineDesign(knots, x, ord, derivs, outer.ok = outer.ok, sparse = sparse) : empty 'derivs'). I have googleized and found some hints like (outer.ok=TRUE) but no one seems to work.
https://r.789695.n4.nabble.com/mgcv-gam-predict-problem-td3411006.html Any idea to make my code work would be appreciated. Here below my new R code : ########################## #Data y=c(34000,45000,19000,48900,65000,67000,78000,90000,51000,32000,54000,85000,38000,76345,87654,90990,78654,67894,56789,65432,18998,78987,67543,45678,76543,67876) x=c(345,543,543,456,432,378,543,579,432,254,346,564,611,543,542,632,345,468,476,487,453,356,490,499,567,532) Dataset=data.frame(y,x) #Plot plot(x,y) #Robust GAM library(robustgam) true.family <- poisson() fit=robustgam(x,y, sp=2424,family=true.family,smooth.basis='ps',K=3) x.new <- seq(range(x)[1], range(x)[2]) robustfit.new <- pred.robustgam(fit, data.frame(X=x.new))$predict.values lines(x.new, robustfit.new, col="green", lwd=2) # To find the « sp » to include in the fit function here above robustfit.gic<-robustgam.GIC.optim(x,y,family=true.family,p=3,c=1.6,show.msg=FALSE,smooth.basis="ps", method="L-BFGS-B") ## CROSS VALIDATION REPLICATIONS MSE ROBUST GAM install.packages("ISLR") library(ISLR) # Create a list to store the results lst<-list() # This statement does the repetitions (looping) for(i in 1 :1000) { n=dim(Dataset)[1] p=0.667 sam=sample(1 :n,floor(p*n),replace=FALSE) Training =Dataset [sam,] Testing = Dataset [-sam,] fit18<-robustgam(x,y, sp=4356,family=true.family,smooth.basis='ps',K=3) ypred=pred.robustgam(fit18,data.frame(X=Testing)) MSE = mean((y-ypred)^2) MSE lst[i]<-MSE } mean(unlist(lst)) #################################### Le dimanche 17 janvier 2021 à 11:41:49 UTC+1, Eric Berger <ericjber...@gmail.com> a écrit : Hi Sacha, I never used these packages before but I installed them and tried your code. I have a few observations that may help. 1. the statement ypred = predict(fit18,newdata=Testing) is wrong. Checkout the help page (?robustgam) which shows in the Examples section at the bottom to use something like ypred = pred.robustgam( fit18, data.frame(X=Testing) 2. your logic is wrong. You define the vectors x and y at the top. They should remain untouched during your program. However in the loop you redefine y and then use the redefined y as an argument to robustgam() the next time through the loop. This looks like a serious error. HTH, Eric On Sun, Jan 17, 2021 at 12:20 PM varin sacha via R-help <r-help@r-project.org> wrote: > Dear R-experts, > > Here below my reproducible R code. I get an error message (end of code) I > can't solve. > Many thanks for your help. > > ########################## > #Data > y=c(34000,45000,19000,48900,65000,67000,78000,90000,51000,32000,54000,85000,38000,76345,87654,90990,78654,67894,56789,65432,18998,78987,67543,45678,76543,67876) > x=c(345,543,543,456,432,378,543,579,432,254,346,564,611,543,542,632,345,468,476,487,453,356,490,499,567,532) > > Dataset=data.frame(y,x) > > #Plot > plot(x,y) > > #Robust GAM > library(robustgam) > true.family <- poisson() > fit=robustgam(x,y, sp=4356,family=true.family,smooth.basis='ps',K=3) > x.new <- seq(range(x)[1], range(x)[2]) > robustfit.new <- pred.robustgam(fit, data.frame(X=x.new))$predict.values > lines(x.new, robustfit.new, col="green", lwd=2) > > # To find the « sp » to include in the fit function here above > robustfit.gic<-robustgam.GIC.optim(x,y,family=true.family,p=3,c=1.6,show.msg=FALSE,smooth.basis="tp", > method="L-BFGS-B") > > ## CROSS VALIDATION REPLICATIONS MSE ROBUST GAM > install.packages("ISLR") > library(ISLR) > > # Create a list to store the results > lst<-list() > > # This statement does the repetitions (looping) > for(i in 1 :1000) > { > > n=dim(Dataset)[1] > p=0.667 > sam=sample(1 :n,floor(p*n),replace=FALSE) > Training =Dataset [sam,] > Testing = Dataset [-sam,] > > fit18<-robustgam(x,y, sp=4356,family=true.family,smooth.basis='ps',K=3) > > ypred=predict(fit18,newdata=Testing) > y=Dataset[-sam,]$y > MSE = mean((y-ypred)^2) > MSE > lst[i]<-MSE > } > mean(unlist(lst)) > #################################### > > > ______________________________________________ > 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. > ______________________________________________ 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.
