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This paper investigates the accuracy of bootstrap-based inference in the case of long memory fractionally integrated processes. The re-sampling method is based on the semi-parametric sieve approach, whereby the dynamics in the process used to produce
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1e97aa6adf372dfc14810b68098400c6
This paper investigates the use of bootstrap-based bias correction of semi-parametric estimators of the long memory parameter in fractionally integrated processes. The re-sampling method involves the application of the sieve bootstrap to data pre-fil
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e963869c4f5dcc66809eab5e6c6f0171
We evaluate the performances of various methods for forecasting tourism data. The data used include 366 monthly series, 427 quarterly series and 518 annual series, all supplied to us by either tourism bodies or academics who had used them in previous
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1c38c587854e80673cef8687883267d7
Autor:
D.S. Poskitt, Wenying Yao
In this article we investigate the theoretical behaviour of finite lag VAR(n) models fitted to time series that in truth come from an infinite order VAR(?) data generating mechanism. We show that overall error can be broken down into two basic compon
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b39fff5a361787847487328fbd5aa63f
Statistical models can play a crucial role in decision making. Traditional model validation tests typically make restrictive parametric assumptions about the model under the null and the alternative hypotheses. The majority of these tests examine one
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::52cd776c9d3640b2b0e51ffb894c8e9d
Vector Autoregresive Moving Average Identification for Macroeconomic Modeling: Algorithms and Theory
Autor:
Poskitt, D.S.
This paper develops a new methodology for identifying the structure of VARMA time series models. The analysis proceeds by examining the echelon canonical form and presents a fully automatic data driven approach to model specification using a new tech
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d8db4f6f4a75e96c9d59b305161be38
One of the most widely used standard procedures for model evaluation in classification and regression is K-fold cross-validation (CV). However, when it comes to time series forecasting, because of the inherent serial correlation and potential non-sta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::81f984a21d51dc7a996305cfdbc92bf2
Autor:
Khan, Md Atikur Rahman, Poskitt, D.S.
In this paper we propose a new methodology for selecting the window length in Singular Spectral Analysis in which the window length is determined from the data prior to the commencement of modeling. The selection procedure is based on statistical tes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::37556ff7c46ca98c4d7958222e3240aa
This research proposes that, in cases where threshold covariates are either unavailable or difficult to observe, practitioners should treat these characteristics as latent, and use simulated maximum likelihood techniques to control for them. Two econ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::141e21eaa3ffa3a119179ed132761bb6
Window Length Selection and Signal-Noise Separation and Reconstruction in Singular Spectrum Analysis
Autor:
Md Atikur Rahman Khan, D.S. Poskitt
In Singular Spectrum Analysis (SSA) window length is a critical tuning parameter that must be assigned by the practitioner. This paper provides a theoretical analysis of signal-noise separation and reconstruction in SSA that can serve as a guide to o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2676bea00618dd5112812ebe517c6023