Existence of long memory in ozone time series

Muzirah Musa, Kamarulzaman Ibrahim

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Long-memory is often observed in time series data. The existence of long-memory in a data set implies that the successive data points are strongly correlated i.e. they remain persistent for quite some time. A commonly used approach in modelling the time series data such as the Box and Jenkins models are no longer appropriate since the assumption of stationary is not satisfied. Thus, the scaling analysis is particularly suitable to be used for identifying the existence of long-memory as well as the extent of persistent data. In this study, an analysis was carried out on the observed daily mean per hour of ozone concentration that were available at six monitoring stations located in the urban areas of Peninsular Malaysia from 1998 to 2006. In order to investigate the existence of long-memory, a preliminary analysis was done based on plots of autocorrelation function (ACF) of the observed data. Scaling analysis involving five methods which included rescaled range, rescaled variance, dispersional, linear and bridge detrending techniques of scaled windowed variance were applied to estimate the Hurst coefficient (H) at each station. The results revealed that the ACF plots indicated a slow decay as the number lag increased. Based on the scaling analysis, the estimated H values lay within 0.7 and 0.9, indicating the existence of long-memory in the ozone time series data. In addition, it was also found that the data were persistent for the period of up to 150 days.

Original languageEnglish
Pages (from-to)1367-1376
Number of pages10
JournalSains Malaysiana
Volume41
Issue number11
Publication statusPublished - Nov 2012

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ozone
time series
autocorrelation
urban area
analysis
modeling

Keywords

  • Hurst coefficient
  • Long-memory
  • Ozone
  • Scaling analysis

ASJC Scopus subject areas

  • General

Cite this

Existence of long memory in ozone time series. / Musa, Muzirah; Ibrahim, Kamarulzaman.

In: Sains Malaysiana, Vol. 41, No. 11, 11.2012, p. 1367-1376.

Research output: Contribution to journalArticle

Musa, M & Ibrahim, K 2012, 'Existence of long memory in ozone time series', Sains Malaysiana, vol. 41, no. 11, pp. 1367-1376.
Musa, Muzirah ; Ibrahim, Kamarulzaman. / Existence of long memory in ozone time series. In: Sains Malaysiana. 2012 ; Vol. 41, No. 11. pp. 1367-1376.
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