[R] Not the same length

varin sacha
Tue, 17 Sep 2019 20:35:48 -0000

Many thanks David, it perfectly works.
Now, one last think.
If I want my R code here below to run let's say B=500 times and at the end I
want to get the average for the MSE_GAM and for the MSE_MARS. How can I do that
?

library(mgcv)
library(earth)
n<-2000
x<-runif(n, 0, 5)
z <- runif(n, 0, 5)
a <- runif(n, 0, 5) ?
y_model<- 0.1*x^3 - 0.5 * z^2 - a + 10
y_obs <- c( rnorm(n*0.5, y_model, 0.1), rnorm(n*0.5, y_model, 0.5) )
 gam_model<- gam(y_obs~s(x)+s(z)+s(a))
 mars_model<-earth(y_obs~x+z+a) ?
MSE_GAM<-mean((gam_model$fitted.values - y_model)^2)
MSE_MARS<-mean((mars_model$fitted.values - y_model)^2) ?
MSE_GAM
MSE_MARS







Le mardi 17 septembre 2019 ? 22:27:54 UTC+2, David Winsemius <dwinsemius at
comcast.net> a ?crit :






On 9/17/19 12:48 PM, varin sacha via R-help wrote:
> Dear R-helpers,
>
> Doing dput(x) and dput(y_obs), the 2 vectors are not the same length (1800
for y_obs and 2000 for x)
> How can I solve the problem ?
>
> Here is the reproducible R code
>
>? ? #? #? #? #? #? #? #? #? #? #
> library(mgcv)
>? library(earth)
>
> n<-2000
> x<-runif(n, 0, 5)
>? y_model<- 0.1*x^3 - 0.5 * x^2 - x + 10
> # y_obs<-rnorm(n*0.9, y_model, 0.1)+rnorm(n*0.1, y_model, 0.5) # maybe
not exactly your goal?


You didn't lay out any goals for analysis, so let me guess what was
intended:


I suspect that you were hoping to model a mixture composed of 90% from
one distribution and 10% from another. If I'm right about that guess
then you would instead wat to join the samples from each distribution:

y_obs<-c( rnorm(n*0.9, y_model, 0.1),? rnorm(n*0.1, y_model, 0.5) )

--

David


> gam_model<- gam(y_obs~s(x))
> mars_model<- earth(y_obs~x)
> MSE_GAM<-mean((gam_model$fitted.values - y_model)^2)
> MSE_MARS<-mean((mars_model$fitted.values - y_model)^2)
> MSE_GAM
> MSE_MARS
>? ? #? #? #? #? #? #? #? #? #? #? #? #? #? #? #? #
>
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