Estimation of parameters of autoregressive models with fractional differences in the presence of additive noise

For modeling in time series, models with fractional differences are widely used. The best known model is the ARFIMA (autoregressive fractionally integrated moving average) model. It is known that for integer-order autoregressive models, autoregressive models with additive noise can outperform ARMA a...

Full description

Saved in:
Bibliographic Details
Main Author: Dmitriy V. Ivanov
Format: Article
Language:English
Published: Samara National Research University 2023-10-01
Series:Вестник Самарского университета: Естественнонаучная серия
Subjects:
Online Access:https://journals.ssau.ru/est/article/viewFile/27075/10253
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849309534075486208
author Dmitriy V. Ivanov
author_facet Dmitriy V. Ivanov
author_sort Dmitriy V. Ivanov
collection DOAJ
description For modeling in time series, models with fractional differences are widely used. The best known model is the ARFIMA (autoregressive fractionally integrated moving average) model. It is known that for integer-order autoregressive models, autoregressive models with additive noise can outperform ARMA and autoregressive models in terms of accuracy. This article considers a class of autoregressive models with fractional order differences. The article presents a new method for estimating parameters autoregressive models with fractional differences in the presence of additive noise with an unknown variance of additive noise. The propose algorithm was realized in Matlab. The simulation results show the high efficiency of the propose algorithm.
format Article
id doaj-art-aee97db41bd747699ca83ee9063352c8
institution Kabale University
issn 2541-7525
2712-8954
language English
publishDate 2023-10-01
publisher Samara National Research University
record_format Article
series Вестник Самарского университета: Естественнонаучная серия
spelling doaj-art-aee97db41bd747699ca83ee9063352c82025-08-20T03:54:07ZengSamara National Research UniversityВестник Самарского университета: Естественнонаучная серия2541-75252712-89542023-10-01293939910.18287/2541-7525-2023-29-3-93-998787Estimation of parameters of autoregressive models with fractional differences in the presence of additive noiseDmitriy V. Ivanov0https://orcid.org/0000-0002-5021-5259Samara National Research UniversityFor modeling in time series, models with fractional differences are widely used. The best known model is the ARFIMA (autoregressive fractionally integrated moving average) model. It is known that for integer-order autoregressive models, autoregressive models with additive noise can outperform ARMA and autoregressive models in terms of accuracy. This article considers a class of autoregressive models with fractional order differences. The article presents a new method for estimating parameters autoregressive models with fractional differences in the presence of additive noise with an unknown variance of additive noise. The propose algorithm was realized in Matlab. The simulation results show the high efficiency of the propose algorithm.https://journals.ssau.ru/est/article/viewFile/27075/10253fractional differenceautoregressive modeltotal least squaresadditive noiseunknown ratio of variancesgeneralized instrumental variableslong run memory
spellingShingle Dmitriy V. Ivanov
Estimation of parameters of autoregressive models with fractional differences in the presence of additive noise
Вестник Самарского университета: Естественнонаучная серия
fractional difference
autoregressive model
total least squares
additive noise
unknown ratio of variances
generalized instrumental variables
long run memory
title Estimation of parameters of autoregressive models with fractional differences in the presence of additive noise
title_full Estimation of parameters of autoregressive models with fractional differences in the presence of additive noise
title_fullStr Estimation of parameters of autoregressive models with fractional differences in the presence of additive noise
title_full_unstemmed Estimation of parameters of autoregressive models with fractional differences in the presence of additive noise
title_short Estimation of parameters of autoregressive models with fractional differences in the presence of additive noise
title_sort estimation of parameters of autoregressive models with fractional differences in the presence of additive noise
topic fractional difference
autoregressive model
total least squares
additive noise
unknown ratio of variances
generalized instrumental variables
long run memory
url https://journals.ssau.ru/est/article/viewFile/27075/10253
work_keys_str_mv AT dmitriyvivanov estimationofparametersofautoregressivemodelswithfractionaldifferencesinthepresenceofadditivenoise