[R] Error in UseMethod("predict")

[Eric Berger]

Hi Sacha,
I took a quick look. Sorry, I don't see immediately what is causing the
problem.
Maybe someone else can help.


On Sun, Jan 17, 2021 at 3:22 PM varin sacha <varinsacha using yahoo.fr> wrote:

> 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 <
> ericjberger using 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 using 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 using r-project.org mailing list -- To UNSUBSCRIBE and more, see
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> > and provide commented, minimal, self-contained, reproducible code.
> >
>
>

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