Re: [chrony-dev] [GIT] chrony/chrony.git branch, master, updated. 1.25-pre1-18-g20a4340

[Miroslav Lichvar <mlichvar@xxxxxxxxxx>]

On Wed, Apr 13, 2011 at 07:55:26PM -0700, Bill Unruh wrote:
> Ok I think I have figured out what is happening. The way in which the weights
> are used in the program is as if a set of w_i measurements were made at the
> point x_i, with each of them yielding the value y_i. But the estimate of the
> standard deviation goes as 1/sqrt(N) where N is the total number of
> measurements. Ie, as the w_i grow, the variance decreases as 1/W=1/sum W_i

Thanks for the analysis.

> As you say this is unstable. I think at present the best thing would be to
> revert to the old 1+(distance_i-Min_dist)/Min_dist. Alternativey you could
> use something like
> 
> M= (Min_dist+sd)
> This essentially makes M the larger of the Min_dist and the standard
> deviation and then divide by that instead of by Min_dist. This means that if
> the stadard deviation is smaller than the min distance, then one uses the
> min distance, but is the standard deviation is larger, then you use that.

I'm not sure I understand how would that help.

> Alternatively you could divide the weights by the mean weight to normalise
> the weights. This should prevent the runaway, but it still leaves open why you
> would divide by sd rather than by the min_dist

I think that would fix only the problem with infinity, the positive
feedback would be still there, i.e. one sample would be more
significant by many orders of magnitute than the rest.

> Ie, I am not at all clear on what the theory is that you are applying in
> deciding that you want to use the standard deviation rather than the min-dist.

See my other mail.

-- 
Miroslav Lichvar

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