Interminable Long Memory Model And Its Hybrid For Time Series Modeling

Alhaji, Jibrin Sanusi (2019) Interminable Long Memory Model And Its Hybrid For Time Series Modeling. PhD thesis, Universiti Sains Malaysia.

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Abstract

The financial and economic indices are nonstationary, long-range dependence and volatile. These are very serious problems because each affect the accuracy, validity and reliability of model fitting and the forecasting of the studied series. In view of this, our current study proposes fractional filter to decompose the nonstationary and Interminable Long Memory (ILM) time series with fractional differencing value in the interval of 1<

Item Type:	Thesis (PhD)
Subjects:	Q Science > QA Mathematics > QA1 Mathematics (General)
Divisions:	Pusat Pengajian Sains Matematik (School of Mathematical Sciences) > Thesis
Depositing User:	Mr Mohammad Harish Sabri
Date Deposited:	17 Jun 2021 13:56
Last Modified:	17 Jun 2021 13:56
URI:	http://eprints.usm.my/id/eprint/49314

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