Smoothed Conditional Scale Function Estimation in AR(1)-ARCH(1) Processes

Smoothed Conditional Scale Function Estimation in AR(1)-ARCH(1) Processes

The estimation of the Smoothed Conditional Scale Function for time series was taken out under the conditional heteroscedastic innovations by imitating the kernel smoothing in nonparametric QAR-QARCH scheme. The estimation was taken out based on the quantile regression methodology proposed by Koenker...

Full description

Bibliographic Details
Main Authors: Lema Logamou Seknewna, Peter Mwita Nyamuhanga, Benjamin Kyalo Muema
Format: Article
Language:English
Published: Hindawi Limited 2018-01-01
Series:Journal of Probability and Statistics
Online Access:http://dx.doi.org/10.1155/2018/4816716
id doaj-0e2759240918480d967fb56e96cc3706
record_format Article
spelling doaj-0e2759240918480d967fb56e96cc37062020-11-24T21:40:40ZengHindawi LimitedJournal of Probability and Statistics1687-952X1687-95382018-01-01201810.1155/2018/48167164816716Smoothed Conditional Scale Function Estimation in AR(1)-ARCH(1) ProcessesLema Logamou Seknewna0Peter Mwita Nyamuhanga1Benjamin Kyalo Muema2Department of Mathematics, Pan African University Institute for Basic Sciences, Technology and Innovation, P.O. Box 62000, Nairobi 00200, KenyaDepartment of Mathematics, Machakos University, P.O. Box 136, Machakos 90100, KenyaDepartment of Statistics and Actuarial Sciences, Jomo Kenyatta University of Agriculture and Technology, P.O. Box 62000, Nairobi 00200, KenyaThe estimation of the Smoothed Conditional Scale Function for time series was taken out under the conditional heteroscedastic innovations by imitating the kernel smoothing in nonparametric QAR-QARCH scheme. The estimation was taken out based on the quantile regression methodology proposed by Koenker and Bassett. And the proof of the asymptotic properties of the Conditional Scale Function estimator for this type of process was given and its consistency was shown.http://dx.doi.org/10.1155/2018/4816716
collection DOAJ
language English
format Article
sources DOAJ
author Lema Logamou Seknewna
Peter Mwita Nyamuhanga
Benjamin Kyalo Muema
spellingShingle Lema Logamou Seknewna
Peter Mwita Nyamuhanga
Benjamin Kyalo Muema
Smoothed Conditional Scale Function Estimation in AR(1)-ARCH(1) Processes
Journal of Probability and Statistics
author_facet Lema Logamou Seknewna
Peter Mwita Nyamuhanga
Benjamin Kyalo Muema
author_sort Lema Logamou Seknewna
title Smoothed Conditional Scale Function Estimation in AR(1)-ARCH(1) Processes
title_short Smoothed Conditional Scale Function Estimation in AR(1)-ARCH(1) Processes
title_full Smoothed Conditional Scale Function Estimation in AR(1)-ARCH(1) Processes
title_fullStr Smoothed Conditional Scale Function Estimation in AR(1)-ARCH(1) Processes
title_full_unstemmed Smoothed Conditional Scale Function Estimation in AR(1)-ARCH(1) Processes
title_sort smoothed conditional scale function estimation in ar(1)-arch(1) processes
publisher Hindawi Limited
series Journal of Probability and Statistics
issn 1687-952X
1687-9538
publishDate 2018-01-01
description The estimation of the Smoothed Conditional Scale Function for time series was taken out under the conditional heteroscedastic innovations by imitating the kernel smoothing in nonparametric QAR-QARCH scheme. The estimation was taken out based on the quantile regression methodology proposed by Koenker and Bassett. And the proof of the asymptotic properties of the Conditional Scale Function estimator for this type of process was given and its consistency was shown.
url http://dx.doi.org/10.1155/2018/4816716
work_keys_str_mv AT lemalogamouseknewna smoothedconditionalscalefunctionestimationinar1arch1processes
AT petermwitanyamuhanga smoothedconditionalscalefunctionestimationinar1arch1processes
AT benjaminkyalomuema smoothedconditionalscalefunctionestimationinar1arch1processes
_version_ 1725925272084021248

Similar Items