Below.
-- Bert
On Fri, Oct 7, 2011 at 1:09 PM, Saurav Pathak <saurav@sas.upenn.edu>
wrote:
> Hi All,
>
> I am trying to use loess to smooth a 2D image, and also obtain the standard
> error for every pixel. I see that the standard error does not make sense.
> For example, running the following:
>
> library(stats)
> x <- array(c(1:100), dim=c(100,100))
> y <- t(x)
> v <- exp(-((x-50)^2+(y-50)^2)/30^2)
> s <- v*0.02
> g_noise <- rnorm(10000, mean = 0, sd = s)
> f <- v + g_noise
> f.loess <- loess(f ~ x + y, span=0.1,
data.frame(x=c(x),y=c(y),f=c(**f)))
> f.predict <- predict(f.loess, data = data.frame(x = c(x), y = c(y), f
> c(f)), span = 0.1,se=TRUE)
> image(1:100,1:100,matrix(f.**predict$se,nrow=100))
>
> I get an image of the standard error that has peaks at regular grid nodes.
> Shouldn't I expect to see roughly the same error that I put in (in
this
> case g_noise)?
No. Apparently you do not know the difference between standard error (of a
fitted value) and standard deviation. I suggest you consult someone who
does.
> I notice that the noise peaks move apart for higher span values.
>
> Thanks for your help!
> Saurav
>
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