Exploring detrending techniques in detecting long-memory of ozone time series in Malaysia by simulation

Muzirah Musa, Abdul Aziz Jemain

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Air pollutants, and specifically ozone in the atmosphere, have received extensive attention since last few decades, mainly because of their adverse effect on people's health. Generally, the collected ozone data are often recorded as time series and long-memory behaviour in ozone levels usually exist. Long-memory or persistency is one of the statistical properties in time series which can be estimated by the Hurst coefficient, H determination. Currently, many methods to estimate H are available. Most of them, even if very effective, need prior information to be applied (in particular about the stationary nature of the series). In order to assess the long-term ozone behaviour in Malaysia, this study aimed to explore the role of detrending techniques of three existing methods used in detecting long-memory. Simulation series in the range of 0.1 ≤ H≤ 0.9 without any assumption on the stationary nature of the time series were used to detect long-memory. The quality of estimation was evaluated in terms of biases and variability. These methods are then applied to the daily mean hourly ozone concentration at 6 monitoring stations in Malaysia over 9 years. Our aim is to plan an optimal procedure to estimate the value of the Hurst coefficient and in addition to explain the degree of persistency in long-term ozone concentration in data Malaysia.

Original languageEnglish
Title of host publicationMODSIM 2011 - 19th International Congress on Modelling and Simulation - Sustaining Our Future: Understanding and Living with Uncertainty
Pages2197-2203
Number of pages7
Publication statusPublished - 2011
Event19th International Congress on Modelling and Simulation - Sustaining Our Future: Understanding and Living with Uncertainty, MODSIM2011 - Perth, WA
Duration: 12 Dec 201116 Dec 2011

Other

Other19th International Congress on Modelling and Simulation - Sustaining Our Future: Understanding and Living with Uncertainty, MODSIM2011
CityPerth, WA
Period12/12/1116/12/11

Fingerprint

Malaysia
Ozone
Long Memory
Time series
Data storage equipment
Simulation
Series
Prior Information
Coefficient
Pollutants
Estimate
Statistical property
Atmosphere
Health
Monitoring
Air
Range of data

Keywords

  • Hurst coefficient
  • Long-memory
  • Ozone
  • Persistency
  • Stationarity

ASJC Scopus subject areas

  • Modelling and Simulation

Cite this

Musa, M., & Jemain, A. A. (2011). Exploring detrending techniques in detecting long-memory of ozone time series in Malaysia by simulation. In MODSIM 2011 - 19th International Congress on Modelling and Simulation - Sustaining Our Future: Understanding and Living with Uncertainty (pp. 2197-2203)

Exploring detrending techniques in detecting long-memory of ozone time series in Malaysia by simulation. / Musa, Muzirah; Jemain, Abdul Aziz.

MODSIM 2011 - 19th International Congress on Modelling and Simulation - Sustaining Our Future: Understanding and Living with Uncertainty. 2011. p. 2197-2203.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Musa, M & Jemain, AA 2011, Exploring detrending techniques in detecting long-memory of ozone time series in Malaysia by simulation. in MODSIM 2011 - 19th International Congress on Modelling and Simulation - Sustaining Our Future: Understanding and Living with Uncertainty. pp. 2197-2203, 19th International Congress on Modelling and Simulation - Sustaining Our Future: Understanding and Living with Uncertainty, MODSIM2011, Perth, WA, 12/12/11.
Musa M, Jemain AA. Exploring detrending techniques in detecting long-memory of ozone time series in Malaysia by simulation. In MODSIM 2011 - 19th International Congress on Modelling and Simulation - Sustaining Our Future: Understanding and Living with Uncertainty. 2011. p. 2197-2203
Musa, Muzirah ; Jemain, Abdul Aziz. / Exploring detrending techniques in detecting long-memory of ozone time series in Malaysia by simulation. MODSIM 2011 - 19th International Congress on Modelling and Simulation - Sustaining Our Future: Understanding and Living with Uncertainty. 2011. pp. 2197-2203
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