[R] understanding predict.lm
Spencer Graves
@pencer@gr@ve@ @end|ng |rom e||ect|vede|en@e@org
Mon Nov 6 22:16:33 CET 2023
Hello, All:
I am unable to manually replicate predict.lm, specifically comparing
se.fit with (fit[,3]-fit[,2]): I think their ratio should be
2*qnorm((1-level)/2), and that's not what I'm getting.
Consider the following slight modification of the first example in
help('predict.lm'):
set.seed(1)
x <- rnorm(15)
y <- x + rnorm(15)
predict(lm(y ~ x))
new <- data.frame(x = seq(-3, 3, 0.5))
predict(lm(y ~ x), new, se.fit = TRUE)
pred.w.plim <- predict(lm(y ~ x), new, interval = "prediction",
se.fit = TRUE)
pred.w.clim <- predict(lm(y ~ x), new, interval = "confidence",
se.fit = TRUE)
(z.confInt <- with(pred.w.clim, (fit[,3]-fit[,2])/se.fit))
pnorm(-z.confInt/2)
s.pred <- sqrt(with(pred.w.plim,
se.fit^2+residual.scale^2))
(z.predInt <- with(pred.w.plim, (fit[,3]-fit[,2])/s.pred))
pnorm(-z.predInt/2)
** This gives me 0.01537207. I do not understand why it's not 0.025
with level = 0.95.
Can someone help me understand this?
Thanks,
Spencer Graves
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