[R] Missing variable in new dataframe for prediction

[LE TERTRE Alain]

Hi,
I'm using a loop to evaluate several models by taking adjacent variables from my dataframe.
When i try to get predictions for new values, i get an error message about a missing variable in my new dataframe.

Below is an example adapted from ?gam in mgcv package
library(mgcv)
set.seed(0) 
n<-400
sig<-2
x0 <- runif(n, 0, 1)
x1 <- runif(n, 0, 1)
x2 <- runif(n, 0, 1)
x3 <- runif(n, 0, 1)
f0 <- function(x) 2 * sin(pi * x)
f1 <- function(x) exp(2 * x)
f2 <- function(x) 0.2*x^11*(10*(1-x))^6+10*(10*x)^3*(1-x)^10
f3 <- function(x) 0*x
f <- f0(x0) + f1(x1) + f2(x2)
e <- rnorm(n, 0, sig)
y <- f + e
Mydata<-data.frame(y=y,x0=x0,x1=x1,x2=x2,x3=x3)
remove(list=c("y","x0","x1","x2","x3"))

# Note below the syntax of the 3rd variable required for my loop
for (i in 4:5){
 b<-gam(y~s(x0)+ s(x1)+ ns(Mydata[,i], 3), data=Mydata)

newd <- data.frame(x0=(0:399)/30,x1=(0:399)/30,x2=(0:399)/30,x3=(0:399)/30)
pred <- predict.gam(b,newd)
}
Erreur dans model.frame(formula, rownames, variables, varnames, extras, extranames,  : 
        type (list) incorrect pour la variable 'Mydata'
De plus : Warning message:
not all required variables have been supplied in  newdata!
 in: predict.gam(b, newd) 

#Defining the name for the variable as in the gam function doesn't solve the problem 
 newd <- data.frame(x0=(0:399)/30,x1=(0:399)/30,x2=(0:399)/30,"Mydata[,i]"=(0:399)/30)

Erreur dans model.frame(formula, rownames, variables, varnames, extras, extranames,  : 
        type (list) incorrect pour la variable 'Mydata'
De plus : Warning message:
not all required variables have been supplied in  newdata!
 in: predict.gam(b, newd) 

How should i define my new dataset to be able to get my predictions ?

Thanks in advance


O__ ---- Alain Le Tertre
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