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Diffstat (limited to 'man/massart97ex3.Rd')
-rw-r--r-- | man/massart97ex3.Rd | 14 |
1 files changed, 9 insertions, 5 deletions
diff --git a/man/massart97ex3.Rd b/man/massart97ex3.Rd index 2618709..eb00e79 100644 --- a/man/massart97ex3.Rd +++ b/man/massart97ex3.Rd @@ -23,18 +23,22 @@ m <- lm(y ~ x,w=weights) inverse.predict(m, 15, ws = 1.67) inverse.predict(m, 90, ws = 0.145) -calplot(m) +# Some of the following examples are commented out, because the require +# prediction intervals from predict.lm for weighted models, which is not +# available in R at the moment. + +#calplot(m) m0 <- lm(y ~ x) lod(m0) -lod(m) +#lod(m) # Now we want to take advantage of the lower weights at lower y values -m2 <- lm(y ~ x, w = 1/y) +#m2 <- lm(y ~ x, w = 1/y) # To get a reasonable weight for the lod, we need to estimate it and predict # a y value for it -yhat.lod <- predict(m,data.frame(x = lod(m2))) -lod(m2,w=1/yhat.lod,k=3) +#yhat.lod <- predict(m,data.frame(x = lod(m2))) +#lod(m2,w=1/yhat.lod,k=3) } \source{ Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S., Lewi, P.J., |