R help - May 2020 - Replication : How to get only 1 value

Dear R-experts,

My goal is to get only 1 value : the average/ the mean of the 100 MSE values.
How can I finish my R code ?

###################################################################
my.experiment <- function()? {

n<-500
x<-runif(n, 0, 5)
z <- rnorm(n, 2, 3)
a <- runif(n, 0, 5) 

y_model<- 0.1*x^3 - 0.5 * z^2 - a + 10
y_obs <- y_model +c( rnorm(n*0.97, 0, 0.1), rnorm(n*0.03, 0, 0.5) )
fit1<- lm(y_obs~x^3+z^2+a)

MSE<-mean((fit1$fitted.values - y_model)^2)
return( c(MSE) )
}

my.data = t(replicate( 100, my.experiment() ))
summary(my.data)
################################################################

Hello,

That's just

mean(my.data)

Note that

summary(t(my.data))

also gives the mean. (You need to transpose because the way you ran 
replicate outputs a 1x100 matrix.)


Hope this helps,

Rui Barradas


?s 21:17 de 07/05/20, varin sacha via R-help escreveu:
> Dear R-experts,
> 
> My goal is to get only 1 value : the average/ the mean of the 100 MSE
values. How can I finish my R code ?
> 
> ###################################################################
> my.experiment <- function()? {
> 
> n<-500
> x<-runif(n, 0, 5)
> z <- rnorm(n, 2, 3)
> a <- runif(n, 0, 5)
> 
> y_model<- 0.1*x^3 - 0.5 * z^2 - a + 10
> y_obs <- y_model +c( rnorm(n*0.97, 0, 0.1), rnorm(n*0.03, 0, 0.5) )
> fit1<- lm(y_obs~x^3+z^2+a)
> 
> MSE<-mean((fit1$fitted.values - y_model)^2)
> return( c(MSE) )
> }
> 
> my.data = t(replicate( 100, my.experiment() ))
> summary(my.data)
> ################################################################
> 
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