[Rd] Call for suggestions

From: michael meyer <mjhmeyer_at_googlemail.com>
Date: Sun, 04 Jul 2010 13:55:45 +0200


If this is not the appropriate place to post this question please let me know where
to post it.

I have a package under development which fits models of the form

f(t)=\sum_i B_iG_i(t,\omega)

depending on a parameter vector $\omega$ of arbitrary dimension to data (one dimensional time series) in the general framework of the

data = deterministic signal + Gaussian noise

in the spirit of
Bretthorst, G. Larry, 1988, "Bayesian Spectrum Analysis and Parameter Estimation,"
Lecture Notes in Statistics, vol. 48, Springer-Verlag, New York. The basic parametric model

G_i(t,\omega)=cos(\omega_i t), sin(\omega_i t)

corresponds to classical spectral analysis, however the model can (at least in principle)
be completely general. The problem is that the models cannot be defined by the user but
have to be hard coded (in C++ since the computations are substantial).

I plan to include the ability to modify each model by the action of further parameters as:

time changes: t -> t+omega, t -> omega*t, t -> t^omega model function change: G(t) -> sign(G(t))*|G(t)|^omega

I plan to include models that can be generated by these actions from trig functions,
some piecewise linear functions, monomials, and exponential function. My question is: what further parametric models are of sufficiently general interest to be

Many thanks,

Michael Meyer

        [[alternative HTML version deleted]]

R-devel_at_r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-devel Received on Sun 04 Jul 2010 - 21:07:40 GMT

Archive maintained by Robert King, hosted by the discipline of statistics at the University of Newcastle, Australia.
Archive generated by hypermail 2.2.0, at Mon 05 Jul 2010 - 07:00:11 GMT.

Mailing list information is available at https://stat.ethz.ch/mailman/listinfo/r-devel. Please read the posting guide before posting to the list.

list of date sections of archive