Difference-Based High-Dimensional Long-Run Covariance Matrix Estimation for Mean-shift Time Series
均值变化时间序列的差分型高维长期协方差矩阵估计
We consider estimation of high-dimensional long-run covariance matrices for time series with nonconstant means, a setting in which conventional estimators can be severely biased. To address this difficulty, we propose a difference-based initial estimator that is robust to a broad class of mean variations, and combine it with hard thresholding, soft thresholding, and tapering to obtain sparse long-run covariance estimators for high-dimensional data. We derive convergence…