[SciPy-User] [OT] Bayesian vs. frequentist

Charles R Harris charlesr.harris@gmail....
Tue Feb 14 20:10:39 CST 2012

On Tue, Feb 14, 2012 at 6:25 PM, <josef.pktd@gmail.com> wrote:

> On Tue, Feb 14, 2012 at 4:22 PM, Phil Austin <paustin@eos.ubc.ca> wrote:
> > On 12-02-14 12:39 PM, Sturla Molden wrote:
> >>  On 14.02.2012 21:24, josef.pktd@gmail.com wrote:
> >>
> >> > Do you expect an argument? sounds a bit like http://andrewgelman.com/
> >>
> >
> > Coincidentally, this discussion:
> >
> http://andrewgelman.com/2012/02/adding-an-error-model-to-a-deterministic-model/
> > started when a civil engineering PhD posted a request for help.  My
> reading
> > of the ensuing discussion of both posts is that there is still a lot of
> > work to
> > do in bridging statistics (bayesian or frequentist) and deterministic
> > modeling
> > of complex systems.
> I don't quite see why there should be anything deterministic (in the
> sense of correctly described by a mathematical model) about the growth
> of bacteria and the response of living tissue, (as there is nothing
> deterministic in the behavior of the macro economy). In economics we
> just add a noise variable (unexplained environmental or behavioral
> shocks) everywhere.
> I thought these were exactly the kind of dynamic problems that Kalman
> Filter (or it's nonlinear successors) were invented for.
> My main impression of the two articles and discussion is that being a
> Bayesian is a lot of work if you need to have a fully specified prior
> and likelihood, instead of just working with some semi-parametric
> estimation method (like least squares) that still produces results
> even if you don't have a fully specified likelihood. (It might not be
> efficient compared to the case when you have full information, but
> your results are less wrong than if your full specification is wrong.)
Well, invented priors can be used to bias parametric results for political
purposes. Thar's gold in them priors. So there is that ;)

I read E. T. Jaynes early papers and his book and enjoyed them, but I think
treating physical entropy by Bayesian methods was a bit much. I don't think
think the thermodynamic properties of a system depend on the observers
knowlege. I would say both methods have their place, just use the right one
for the problem at hand.

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