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Structural Break or Long Memory: an Empirical Survey on Daily Rainfall Data Sets Across Malaysia : Volume 17, Issue 4 (08/04/2013)

By Yusof, F.

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Book Id: WPLBN0004010709
Format Type: PDF Article :
File Size: Pages 8
Reproduction Date: 2015

Title: Structural Break or Long Memory: an Empirical Survey on Daily Rainfall Data Sets Across Malaysia : Volume 17, Issue 4 (08/04/2013)  
Author: Yusof, F.
Volume: Vol. 17, Issue 4
Language: English
Subject: Science, Hydrology, Earth
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Historic
Publication Date:
2013
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Yusop, Z., Kane, I. L., & Yusof, F. (2013). Structural Break or Long Memory: an Empirical Survey on Daily Rainfall Data Sets Across Malaysia : Volume 17, Issue 4 (08/04/2013). Retrieved from http://www.ebooklibrary.org/


Description
Description: Department of Mathematical Sciences, Faculty of Science University of Technology Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia. A short memory process that encounters occasional structural breaks in mean can show a slower rate of decay in the autocorrelation function and other properties of fractional integrated I (d) processes. In this paper we employed a procedure for estimating the fractional differencing parameter in semiparametric contexts proposed by Geweke and Porter-Hudak (1983) to analyse nine daily rainfall data sets across Malaysia. The results indicate that all the data sets exhibit long memory. Furthermore, an empirical fluctuation process using the ordinary least square (OLS)-based cumulative sum (CUSUM) test for the break date was applied. Break dates were detected in all data sets. The data sets were partitioned according to their respective break date, and a further test for long memory was applied for all subseries. Results show that all subseries follows the same pattern as the original series. The estimate of the fractional parameters d1 and d2 on the subseries obtained by splitting the original series at the break date confirms that there is a long memory in the data generating process (DGP). Therefore this evidence shows a true long memory not due to structural break.

Summary
Structural break or long memory: an empirical survey on daily rainfall data sets across Malaysia

Excerpt
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