1 citations · 2 across the 6 of their papers we have counts for
7 papers
Mean Independent Component Analysis for Multivariate Time Series
Chung Eun Lee, Zeda Li
In this article, we introduce the mean independent component analysis for multivariate time series to reduce the parameter space. In particular, we seek for a contemporaneous linea…
A Cepstral Model for Efficient Spectral Analysis of Covariate-dependent Time Series
Zeda Li, Yuexiao Dong
This article introduces a novel and computationally fast model to study the association between covariates and power spectra of replicated time series. A random covariate-dependent…
Adaptive Bayesian Sum of Trees Model for Covariate Dependent Spectral Analysis
Yakun Wang, Zeda Li, Scott A. Bruce
This article introduces a flexible and adaptive nonparametric method for estimating the association between multiple covariates and power spectra of multiple time series. The propo…
Classification of Categorical Time Series Using the Spectral Envelope and Optimal Scalings
Zeda Li, Scott A. Bruce, Tian Cai
This article introduces a novel approach to the classification of categorical time series under the supervised learning paradigm. To construct meaningful features for categorical t…
Adaptive Bayesian Spectral Analysis of High-dimensional Nonstationary Time Series
Zeda Li, Ori Rosen, Fabio Ferrarelli +1
This article introduces a nonparametric approach to spectral analysis of a high-dimensional multivariate nonstationary time series. The procedure is based on a novel frequency-doma…
Adaptive Bayesian Power Spectrum Analysis of Multivariate Nonstationary Time Series
Zeda Li, Robert T. Krafty
This article introduces a nonparametric approach to multivariate time-varying power spectrum analysis. The procedure adaptively partitions a time series into an unknown number of a…