Sparse transition matrix estimation for high-dimensional and locally stationary vector autoregressive models

DOI10.1214/17-EJS1325zbMath1403.62159arXiv1604.04002MaRDI QIDQ2412259

Xiaohui Chen, Ziyi Qiu, Xin Ding

Publication date: 23 October 2017

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1604.04002

zbMATH Keywords

kernel smoothingtime-varying parameterslocally stationary processessparsityhigh-dimensionvector autoregression

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20) Applications of statistics to actuarial sciences and financial mathematics (62P05)

Related Items (5)

Change points detection and parameter estimation for multivariate time series ⋮ Time series graphical Lasso and sparse VAR estimation ⋮ Forecasting vector autoregressions with mixed roots in the vicinity of unity ⋮ Inverse covariance operators of multivariate nonstationary time series ⋮ Boosting high dimensional predictive regressions with time varying parameters

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