On Wed, Jun 29, 2016 at 08:04:44AM -0700, Bill Unruh wrote:
On Wed, 29 Jun 2016, Miroslav Lichvar wrote:
I'm very interested in implementing some estimation of the asymmetry
to chrony. I'd like to allow any slope between -0.5 and 0.5, not just
one of the three values (-0.5, 0.0, +0.5). One idea I had was to
search for a value which minimizes the variance in the linear
regression when all points have a constant weight. With each new
sample, the asymmetry would be estimated first and then the offsets
would be adjusted for the weighted regression which is currently used
to estimate the offset. Basically I'm looking for a constant A between
-0.5 and 0.5 which minimizes the variance in linear regression of
points (x, y + A * d), where x is time, y is the symmetric offset and
d is the increase in delay over the minimum. Can A be calculated
directly from (x, y, d) samples? I suspect it would have to be an
iterative approach and this might be expensive.
No, that would just be a two, instead of one, variable linear regression,
One would just minimize (y-C(x-x0)+Ad)^2 over C, x0 and A. Still linear
equations.
Oh, that's great. Thanks. I'll try that. I suspect we will need to use
a long-term average of the slope to prevent adding more noise when the
number of samples is small. If this works well, there will probably be
other interesting problems with "asymmetric" offset that will need to
be addresses. For instance the error interval used in the source
selection would shift, which could be a problem for detection of
falsetickers. The code will likely have to work with both offsets
depending on the context. There is also a question how they should be
reported in chronyc and the logs, and how much confusion this will
create.
--
Miroslav Lichvar
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