[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.

Chuck
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