moving average

MZ — Thu, 20 Aug 2009 04:45:54 -0400

I have paired (x,y) data. I want to compute a sort of moving average on
it, and I want values returned at the same values of x. The kink is
that the x data is not equally spaced.

I've solved the problem this way:

y =
ksdensity(x,x,'kernel','box','weights',y)./ksdensity(x,x,'kernel','box');

But it's dreadfully slow. I have to call ksdensity twice, once with
weighting and once without. The first one is to basically sum the
points within a kernel and the second one is to count the points within
a kernel. (ie. mean=sum/N)

[The size of the kernel isn't terribly important, so I've stuck with the
defaults.]

Is there a better way to do this? I thought about rounding +
convolution, but it would require interpolation and I'm not sure how
willing I am to put up with roundoff error. Although at this stage, it
might be worth it...

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moving average