Title :
The effect of missing data on robust Bayesian spectral analysis
Author :
Christmas, Jacqueline
Author_Institution :
Dept. of Comput. Sci., Univ. of Exeter, Exeter, UK
Abstract :
We investigate the effects of missing observations on the robust Bayesian model for spectral analysis introduced by Christmas [2013]. The model assumes Student-t distributed noise and uses an automatic relevance determination prior on the precisions of the amplitudes of the component sinusoids and it is not obvious what their effect will be when some of the otherwise temporally uniformly sampled data is missing.
Keywords :
belief networks; spectral analysis; automatic relevance determination; missing data effect; missing observations effects; robust Bayesian model; robust Bayesian spectral analysis; student-t distributed noise; Bayes methods; Computational modeling; Data models; Noise; Spectral analysis; Standards; Uncertainty; Bayesian methods; Fourier series; amplitude estimation; discrete Fourier transforms; parameter estimation; phase estimation;
Conference_Titel :
Machine Learning for Signal Processing (MLSP), 2013 IEEE International Workshop on
Conference_Location :
Southampton
DOI :
10.1109/MLSP.2013.6661980
