[SciPy-user] optimization advice needed
David Cournapeau
david@ar.media.kyoto-u.ac...
Mon Jan 28 21:10:18 CST 2008
Andrew Straw wrote:
> If f() is stationary and you are trying to estimate a and b, isn't this
> exactly the case of a Kalman filter for linear f()? And if f() is
> non-linear, there are extensions to the Kalman framework to handle this.
>
Even Kalman is overkill, I think, no (if f is linear) ? A simple wiener
filter may be enough, then.
Neal, I think the solution will depend on your background and how much
time you want to spend on it (as well as the exact nature of the problem
you are solving, obviously, such as can you first estimate the model on
some data offline, and after estimate new data online, etc...): if you
have only a couple of hours to spend, and you don't have background in
bayesian statistics, I think it will be overkill.
A good introduction in the spirit of what Gael suggested (as I
understand it) is to read the first chapter and third chapter of the
book "pattern recognition and machine learning" by C. Bishop. That's the
best, almost self-contained introduction I can think of on the top of my
head.
cheers,
David
More information about the SciPy-user
mailing list