Bayesian Nonparametric Shrinkage Applied to Cepheid Star Oscillations

Details Bayesian Nonparametric Shrinkage Applied to Cepheid Star Oscillations Bayesian Nonparametric Shrinkage Applied to Cepheid Star Oscillations

2012-03-21

arxiv.org/abs/1203.4690v1

Statistical Science 2012, Vol. 27, No. 1, 3-10

Statistics

Methodology

Published in at http://dx.doi.org/10.1214/11-STS384 the Statistical Science (http://www.imstat.org/sts/) by the Institute of M

Scientific paper

10.1214/11-STS384

Bayesian nonparametric regression with dependent wavelets has dual shrinkage properties: there is shrinkage through a dependent prior put on functional differences, and shrinkage through the setting of most of the wavelet coefficients to zero through Bayesian variable selection methods. The methodology can deal with unequally spaced data and is efficient because of the existence of fast moves in model space for the MCMC computation. The methodology is illustrated on the problem of modeling the oscillations of Cepheid variable stars; these are a class of pulsating variable stars with the useful property that their periods of variability are strongly correlated with their absolute luminosity. Once this relationship has been calibrated, knowledge of the period gives knowledge of the luminosity. This makes these stars useful as "standard candles" for estimating distances in the universe.

Affiliated with

Also associated with

No associations

Rating

Bayesian Nonparametric Shrinkage Applied to Cepheid Star Oscillations does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Bayesian Nonparametric Shrinkage Applied to Cepheid Star Oscillations, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Bayesian Nonparametric Shrinkage Applied to Cepheid Star Oscillations will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-488429