Displaying 1 result from an estimated 1 matches for "sefit".
Did you mean:
refit
2012 Mar 24
0
Loess CI
...abs(x1 - x0) # distance from focal x
h <- sort(dist1)[.4*length(x1)] # bandwidth for span: bandwidth =
span*length(x1)
inwindow <- dist1 <= h # observations within window
d <- dist1[dist1 <= h]
z <- d/h
w1 <- (1-abs(z)^3)^3
w2 <- sum(w1^2)
s*sqrt(w2) # calculated sefit
> s*sqrt(w2)
[1] 8.052887
this is quite high, and r gives me
> predict(lo1, se=T)$se.fit[1]
1
0.6055714
although I did calculate s correctly
> lo1$s
[1] 1.484307
> s
[1] 1.484307
So clearly something is wrong with the weight part of my equation. I'm not
sure whether...