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What is Estimating Time-Varying Infinite Memory Processes about?

This paper extends kernel-based estimation techniques to infinite memory processes, such as locally stationary AR(∞) and GARCH models. It establishes uniform consistency and asymptotic normality for these estimators and demonstrates their effectiveness through numerical experiments on simulated and real datasets. The findings provide a framework for analyzing time-varying processes with infinite memory, broadening the scope of existing statistical methods in this area.

Author

firas hmdi

Language

EN