R help - Jan 2021 - Get 3 values not only 1

Dear R-experts,

Here below my R code working but I would like to get 3 values not only 1. The
value I get is, according to my R code, the variance value. My goal is to get 3
values : the bias value, the variance value and the MSE value. How to solve my
problem ?

Many thanks.

####################
# Data
PIB.hab<-c(12000,34000,25000,43000,12500,32400,76320,45890,76345,90565,76580,45670,23450,34560,65430,65435,56755,87655,90755,45675)
ISQ.2018<-c(564,587,489,421,478,499,521,510,532,476,421,467,539,521,478,532,449,487,465,500)

Dataset=data.frame(ISQ.2018,PIB.hab) 

#plot
plot(ISQ.2018,PIB.hab)
plot(ISQ.2018,PIB.hab, main="Droite de r?gression lin?aire",
xlab="Score ISQ 2018", ylab="PIB/hab")

#OLS fit
fit1<-lm(PIB.hab~ISQ.2018)
lines(ISQ.2018, fitted(fit1), col="blue", lwd=2)

# 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,]
fit2<-lm(PIB.hab~ISQ.2018) 
ypred<-predict(fit2,newdata=Testing)
y<-Dataset[-sam,]$PIB.hab
MSE <- mean((y-ypred)^2)
biais <- mean(ypred-y)
variance <-mean((ypred- mean(ypred))^2)

lst[i]<-MSE
lst[i]<-biais
lst[i]<-variance

}
mean(unlist(lst))
####################

Hi varin,
How about this:

Mbv<-data.frame(MSE=rep(NA,1000),
 biais=rep(NA,1000),variance=rep(NA,1000))
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,]
 fit2<-lm(PIB.hab~ISQ.2018)
 ypred<-predict(fit2,newdata=Testing)
 y<-Dataset[-sam,]$PIB.hab
 Mbv$MSE[i] <- mean((y-ypred)^2)
 Mbv$biais[i] <- mean(ypred-y)
 Mbv$variance[i] <-mean((ypred- mean(ypred))^2)
}

You can then do what you wish to the data frame Mbv.

Jim

On Thu, Jan 28, 2021 at 7:37 AM varin sacha via R-help
<r-help at r-project.org> wrote:
>
> Dear R-experts,
>
> Here below my R code working but I would like to get 3 values not only 1.
The value I get is, according to my R code, the variance value. My goal is to
get 3 values : the bias value, the variance value and the MSE value. How to
solve my problem ?
>
> Many thanks.

Is this what you are after?  You need to store a vector in the list:
> ####################
> # Data
>
PIB.hab<-c(12000,34000,25000,43000,12500,32400,76320,45890,76345,90565,76580,45670,23450,34560,65430,65435,56755,87655,90755,45675)
>
ISQ.2018<-c(564,587,489,421,478,499,521,510,532,476,421,467,539,521,478,532,449,487,465,500)
>
> Dataset=data.frame(ISQ.2018,PIB.hab)
>
> #plot
> plot(ISQ.2018,PIB.hab)
> plot(ISQ.2018,PIB.hab, main="Droite de r?gression lin?aire",
xlab="Score ISQ 2018", ylab="PIB/hab")
>
> #OLS fit
> fit1<-lm(PIB.hab~ISQ.2018)
> lines(ISQ.2018, fitted(fit1), col="blue", lwd=2)
>
> # 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,]
+   fit2<-lm(PIB.hab~ISQ.2018)
+   ypred<-predict(fit2,newdata=Testing)
+   y<-Dataset[-sam,]$PIB.hab
+   MSE <- mean((y-ypred)^2)
+   biais <- mean(ypred-y)
+   variance <-mean((ypred- mean(ypred))^2)
+
+   lst[[i]] <- c(MSE = MSE,
+                    biais = biais,
+                    variance = variance)
+   # lst[i]<-MSE
+   # lst[i]<-biais
+   # lst[i]<-variance
+
+ }
>
> # convert to a matrix
>
> x <- as.matrix(do.call(rbind, lst))
> colMeans(x)
           MSE         biais      variance
  5.418175e+08 -4.524548e+01  6.321856e+07
>
Jim Holtman
Data Munger Guru

What is the problem that you are trying to solve?
Tell me what you want to do, not how you want to do it.


Jim Holtman
Data Munger Guru

What is the problem that you are trying to solve?
Tell me what you want to do, not how you want to do it.


On Wed, Jan 27, 2021 at 12:37 PM varin sacha via R-help
<r-help at r-project.org> wrote:
>
> Dear R-experts,
>
> Here below my R code working but I would like to get 3 values not only 1.
The value I get is, according to my R code, the variance value. My goal is to
get 3 values : the bias value, the variance value and the MSE value. How to
solve my problem ?
>
> Many thanks.
>
> ####################
> # Data
>
PIB.hab<-c(12000,34000,25000,43000,12500,32400,76320,45890,76345,90565,76580,45670,23450,34560,65430,65435,56755,87655,90755,45675)
>
ISQ.2018<-c(564,587,489,421,478,499,521,510,532,476,421,467,539,521,478,532,449,487,465,500)
>
> Dataset=data.frame(ISQ.2018,PIB.hab)
>
> #plot
> plot(ISQ.2018,PIB.hab)
> plot(ISQ.2018,PIB.hab, main="Droite de r?gression lin?aire",
xlab="Score ISQ 2018", ylab="PIB/hab")
>
> #OLS fit
> fit1<-lm(PIB.hab~ISQ.2018)
> lines(ISQ.2018, fitted(fit1), col="blue", lwd=2)
>
> # 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,]
> fit2<-lm(PIB.hab~ISQ.2018)
> ypred<-predict(fit2,newdata=Testing)
> y<-Dataset[-sam,]$PIB.hab
> MSE <- mean((y-ypred)^2)
> biais <- mean(ypred-y)
> variance <-mean((ypred- mean(ypred))^2)
>
> lst[i]<-MSE
> lst[i]<-biais
> lst[i]<-variance
>
> }
> mean(unlist(lst))
> ####################
>
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