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res1
2013 Feb 26
2
Efficient way to perform linear regressions
...-------------------------------------------------------------------------------------------------
M = matrix( NA, nrow = 10^4, ncol = 200)
for (i in 1:10^4)
{
M[i,] = sample(c(0,1), size=200, replace = T)
}
X = cbind( rnorm(200,1,10) ,1:200, sample(1:10^5,200,T))
Y = rnorm(200)
# loop version
resu1=matrix(NA,nrow=10^4, ncol=2)
resu2=matrix(NA,nrow=10^4, ncol=2)
resu3=matrix(NA,nrow=10^4, ncol=2)
resu4=matrix(NA,nrow=10^4, ncol=2)
t1 = proc.time()
for (i in 1:10^4)
{
fit.ls = lsfit( x = X[M[i,],], y = Y[M[i,]], intercept=F)
resu1[i,] = c( fit.ls$coeff[2], sum((fit.ls$res)^2))
}
t2 = proc.t...
2003 Dec 01
0
No subject
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