[R] loess problems
Liaw, Andy
andy_liaw at merck.com
Sat Feb 5 22:17:02 CET 2005
The problem is that 90% of your data sit on the boundary. Loess is a
nearest neighbor smoother (using (100 x span) % of the data to estimate at
each point). If you call loess() directly with span=2/3 (the default in
scatter.smooth), or something smaller than about 0.91, you'll see that it
has trouble.
Strangely, if you set span=.8, scatter.smooth() will also complain, but not
at the default span... (Re-generating the data yet again does trigger the
warnings, so seems like it does catches things some of the time.)
For your second example, I think loess becomes undefined when the span is
set too small (and 1/n is surely too small): You are asking the algorithm
to take the nearest 1/n of the data to do the smooth. You would think that
should just mean _the_ nearest data point, but the problem is:
> n <- 100
> 1 / n < 1
[1] TRUE
so you're asking the algoithm to take fewer than 1 data point to estimate at
each point. The warnings you see for that example is pointing you in the
right direction.
Andy
> From: Jean Eid
>
> I have a problem either understanding what loess is doing or
> that loess
> has a problem itself.
>
> As the x-axis variables become more concentrated on a
> particular point,the
> estimated loess tends to zero????. the examples below show what i am
> talking about, why is that? my intution tells me
> that it should tend to the mean of the variable which is been
> smoothed.
>
> Here's a worked up example
>
> x <- c(seq(0,100), rep(100,1000))
> y <- rnorm(length(x), mean=10, sd=2)
> scatter.smooth(x,y)
>
>
>
> Although it does give warnings, I don't understand why it is
> giving the
> estimate as zero.
>
>
> another example would be
>
> x <- seq(0,100)
> y <- rnorm(length(x), mean=50, sd=2)
> scatter.smooth(x,y, span=1/length(x))
>
>
> shoudn't this give just the points at which the smoothing algorithm is
> applied?
>
>
>
> thank you
>
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