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*Subject*: Re: efficient kernel or masking algorithm ? UPDATE*From*: "Martin Downing" <martin.downing(at)ntlworld.com>*Date*: Mon, 26 Feb 2001 09:52:18 -0000*Newsgroups*: comp.lang.idl-pvwave*Organization*: ntlworld News Service*References*: <Kocm6.25536$MN.621469@news2-win.server.ntlworld.com> <3A99C6B4.10549265@astro.cornell.edu>*Xref*: news.doit.wisc.edu comp.lang.idl-pvwave:23662

> > interested in this method which is very fast. It is based on the crafty > > formula for variance: > > variance = (sum of the squares)/n + (square of the sums)/n*n > > Righto. I knew I was fishing for something like this. Except I think you mean: > > (population) variance = (sum of the squares)/n - (square of the sums)/n*n > > Luckily, that's how you've coded it too. Sample variance (=population > variance*n/(n-1)) is of course the more common case in science (as opposed to > gambling). Sigh - I hear what you are saying, but this was a misunderstanding. I *tried* to make its use unambiguous by making the default option the absolute variance of the array (n as the denominator) , or when POPULATION_ESTIMATE is set then calculate an *estimate* of the population from which this dataset is assumed to be a SAMPLE [giving (n-1) as the denominator]. Judging by your reply I failed dismally! You are right - POPULATION_ESTIMATE is normally termed "sample stdev" and is the equivalent of IDL's variance(x) - but what they mean is that it is an estimator of the popn stdev! Still waiting to try it in the casinos :) Martin

**References**:**Re: efficient kernel or masking algorithm ? UPDATE***From:*Martin Downing

**Re: efficient kernel or masking algorithm ? UPDATE***From:*John-David Smith

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