Improved estimation method for high dimension semimartingale regression models based on discrete data

In this paper we study a high dimension (Big Data) regression model in continuous time observed in the discrete time moments with dependent noises defined by semimartingale processes. To this end an improved (shrinkage) estimation method is developed and the non-asymptotic comparison between shrinka...

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Veröffentlicht in:	Statistical inference for stochastic processes : an international journal devoted to time series analysis and the statistics of continuous time processes and dynamic systems 2022-10, Vol.25 (3), p.537-576
Hauptverfasser:	Pchelintsev, Evgeny, Pergamenshchikov, Serguei, Leshchinskaya, Maria
Format:	Artikel
Sprache:	eng
Schlagworte:	Asymptotic methods Asymptotic properties Big Data Estimates Gaussian process Mathematics Mathematics and Statistics Nonparametric statistics Probability Theory and Stochastic Processes Regression models Robustness (mathematics) Shrinkage Statistical Theory and Methods
Online-Zugang:	Volltext
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