Shrinkage priors on complex-valued circular-symmetric autoregressive processes

Autor:	Oda, Hidemasa, Komaki, Fumiyasu
Rok vydání:	2020
Předmět:	Mathematics - Statistics Theory 62F15 (Primary) 62C15 (Secondary)
Druh dokumentu:	Working Paper
Popis:	We investigate shrinkage priors on power spectral densities for complex-valued circular-symmetric autoregressive processes. We construct shrinkage predictive power spectral densities, which asymptotically dominate (i) the Bayesian predictive power spectral density based on the Jeffreys prior and (ii) the estimative power spectral density with the maximal likelihood estimator, where the Kullback-Leibler divergence from the true power spectral density to a predictive power spectral density is adopted as a risk. Furthermore, we propose general constructions of objective priors for K\"ahler parameter spaces, utilizing a positive continuous eigenfunction of the Laplace-Beltrami operator with a negative eigenvalue. We present numerical experiments on a complex-valued stationary autoregressive model of order $1$. Comment: revised; Figures are modified
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2004.02389 Zobrazit plný text záznamu View this record from Arxiv