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ols
2010 Jun 29
1
Model validation and penalization with rms package
...uot;, "index.corrected"]
optimism.Rsq[pen] <- val["R-square", "optimism"]
corrected.slope[pen] <- val["Slope", "index.corrected"]
}
plot(corrected.Rsq)
x11(); plot(optimism.Rsq)
x11(); plot(corrected.slope)
p <- pentrace(ols0, penalty=1:60)
ols9 <- ols(y ~ x1 + x2 + x3, penalty=9, x=TRUE, y=TRUE)
validate(ols9, B=200)
index.orig training test optimism index.corrected n
R-square 0.2523404 0.2820734 0.1911878 0.09088563 0.1614548 200
MSE 7.8497722 7.3525300 8.4918212 -1.13929116 8.9890634 200
Inter...