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Statistical inference for ARTFIMA time series with stable innovations

Authors :
Kabala, Jinu
Sabzikar, Farzad
Publication Year :
2021

Abstract

Autoregressive tempered fractionally integrated moving average with stable innovations modifies the power-law kernel of the fractionally integrated time series model by adding an exponential tempering factor. The tempered time series is a stationary model that can exhibits semi-long-range dependence. This paper develops the basic theory of the tempered time series model, including dependence structure and parameter estimation.

Subjects

Subjects :
Statistics - Applications

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2103.07717
Document Type :
Working Paper