Using randomization to improve performance of a variance estimator of strongly dependent errors

• Autorzy: Artur Bryk
• Języki publikacji: EN

Abstrakty

EN

We consider a fixed-design regression model with long-range dependent errors which form a moving average or Gaussian process. We introduce an artificial randomization of grid points at which observations are taken in order to diminish the impact of strong dependence. We estimate the variance of the errors using the Rice estimator. The estimator is shown to exhibit weak (i.e. in probability) consistency. Simulation results confirm this property for moderate and large sample sizes when randomization is employed.

Kategorie tematyczne

• 62G20: Asymptotic properties
• 62G08: Nonparametric regression
• 62M10: Time series, auto-correlation, regression, etc.

• Wydawca: Institute of Mathematics Polish Academy of Sciences
• Czasopismo: Applicationes Mathematicae
• Rocznik: 2012
• Tom: 39
• Numer: 3
• Strony: 273-282

Daty

wydano

2012

Twórcy

autor

Artur Bryk

• Department of Mathematics and Mathematical Economics, Warsaw School of Economics, Al. Niepodległości 162, 02-554 Warszawa, Poland

Identyfikatory

DOI

10.4064/am39-3-2