1 A salient feature of stationary time series analysis is its reliance on the Cholesky decomposition to model temporal dependence and dynamics.
Jul 22, 2020 · Heuristically, one expects for a nearly stationary covariance matrix the entries in each subdiagonal of the Cholesky factor of its inverse to be ...
A block coordinate descent algorithm, where each block is a subdiagonal, is proposed and its convergence is established under mild conditions and simulation ...
Jul 22, 2020 · Smoothness of the subdiagonals of the Cholesky factor of large covariance matrices is closely re- lated to the degrees of nonstationarity of ...
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Jun 16, 2022 · Our paper on "Fused-Lasso Regularized Cholesky Factors of Large Nonstationary Covariance Matrices of Replicated Time Series" has been ...
Abstract. The smoothness of subdiagonals of the Cholesky factor of large covariance matrices is closely related to the degree of nonstationarity of ...
Fused-Lasso Regularized Cholesky Factors of Large Nonstationary Covariance Matrices of Replicated Time Series. Journal of Computational and Graphical ...
Fused-lasso regularized cholesky factors of large nonstationary covariance matrices of replicated time series. A Dallakyan, M Pourahmadi. Journal of ...
Apr 29, 2024 · Fused-Lasso Regularized Cholesky Factors of Large Nonstationary Covariance Matrices of Replicated Time Series. J. Comput. Graph. Stat. 32(1) ...
Fused-lasso regularized cholesky factors of large nonstationary covariance matrices of replicated time series. J. Comput. Graph. Stat. (2022). P. Danaher et ...