Hi all,
I want to make the following:
I want to run a linear regression on each column of a matrix "estima" on
the correspondent column on the matrix "estima2".
You see I want to regress estima[,1] on estima2[,1] this way to all
columns....
At the same time I want to make a regression adding each time a new
observation.
You see, the first regression will regress only one observation with one
observation (I now this has no sense in this only one observation step)
the second turn of observation will make
estima[1:2,n] on estima2[1:2,n] for all "n".
Third stimation will make
estima[1:3,n] on estima2[1:3,n] for all "n".
And so on.
Make this, I want to make an output matrix on each "t-value" associated
with the "regressor".
Conclusion my final matrix called "t value" should include al the t values
on the regression each of them incorporating a new observation, with the
same rows and colums than "estima".
I have tried several thing but I cannot achive.
I writte to see if you can guide me¡¡¡
I swear I´m trying.
randz<-matrix(rnorm(5000),50,100)
H<-matrix(0,50,100)
H[1,]<-randz[1,]
for (i in 2:50){
if(i < 26) {
H[i, ] <- 0.6 * H[i-1, ] + randz[i, ]
} else {
H[i, ] <- H[i-1, ] + randz[i, ]
}
}
write.table(H, file = "datad.txt")
g<-read.table("datad.txt")
hy<-nrow(g)-1
estima<-H[2:nrow(g), ]
estima2<-H[ 1:hy, ]
mycoef <- function (x,y)
a<-estima
b<-estima2
f<-summary(lm(a~b))
ff<-coef(f)
ff[2,"t value"]
tvalue <- sapply (2:ncol(b) , function (i){
y<-a[,i]
x<-b[,i]
mycoef(x,y)
}
)
print (summary(tvalue))
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