Statistics Seminar:: BAYESIAN DECISION THEORETIC SCALE-ADAPTIVE ESTIMATION OF A LOG-SPECTRAL DENSITY

GUEST LECTURER
Dr. Brani Vidakovic

AFFILIATION
Georgia Institute of Technology

ABSTRACT
The problem of estimating the log-spectrum of a
stationary Gaussian time series by Bayesianly induced
shrinkage of empirical wavelet coefficients is studied.
A model in the wavelet domain that
accounts for distributional properties of the log-periodogram
at levels of fine detail and approximate normality at
coarse levels in the wavelet decomposition, is proposed.
The smoothing procedure, called BAMS-LP (Bayesian Adaptive Multiscale
Shrinker of Log-Periodogram),
ensures that the reconstructed log-spectrum is
as noise-free as possible. It is also shown that the resulting
Bayes estimators are asymptotically optimal (in the frequentist sense).


Comparisons with non-wavelet and wavelet-non-Bayesian
methods are discussed.


This is a joint work with Marianna Pensky from UCF.

DATE & TIME
Thursday, March 25, 2004 -- 12:00 PM

DURATION
1 hour

LOCATION
228 ISyE main building

CONTACT PERSON
roshan@isye.gatech.edu