Conditional adaptive Bayesian spectral analysis of nonstationary biomedical time series.

ABSTRACT: Many studies of biomedical time series signals aim to measure the association between frequency-domain properties of time series and clinical and behavioral covariates. However, the time-varying dynamics of these associations are largely ignored due to a lack of methods that can assess the changing nature of the relationship through time. This article introduces a method for the simultaneous and automatic analysis of the association between the time-varying power spectrum and covariates, which we refer to as conditional adaptive Bayesian spectrum analysis (CABS). The procedure adaptively partitions the grid of time and covariate values into an unknown number of approximately stationary blocks and nonparametrically estimates local spectra within blocks through penalized splines. CABS is for

SUBMITTER: Bruce SA 

PROVIDER: S-EPMC5677586 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature