Banded Regularization of Autocovariance Matrices in Application to Parameter Estimation and Forecasting of Time Series
自协方差矩阵的带状正则化：时间序列参数估计与预测
Summary The paper addresses a ‘large p–small n’ problem in a time series framework and considers properties of banded regularization of an empirical autocovariance matrix of a time series process. Utilizing the banded autocovariance matrix enables us to fit a much longer auto-regressive AR(p) model to the observed data than typically suggested by the Akaike information criterion, while controlling how many parameters are to be estimated precisely and the level of accuracy.…