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Long memory analysis in DNA sequences

Author

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  • Lopes, S.R.C.
  • Nunes, M.A.

Abstract

Our goal in this work is to construct empirical confidence intervals for the fractional parameter d in ARFIMA(0,d,0) processes. Through these confidence intervals one can compare several estimators for d to decide which one is the best estimation method related to long memory time series. We use a fortran routine that simulates random time series to later perform an analysis for detecting long memory. We also apply the methodology to real DNA sequences to evaluate the efficiency of our method in the construction of these confidence intervals.

Suggested Citation

  • Lopes, S.R.C. & Nunes, M.A., 2006. "Long memory analysis in DNA sequences," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 361(2), pages 569-588.
    • Handle: RePEc:eee:phsmap:v:361:y:2006:i:2:p:569-588
    DOI: 10.1016/j.physa.2005.06.099
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    References listed on IDEAS

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    1. Weron, Rafał, 2002. "Estimating long-range dependence: finite sample properties and confidence intervals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 312(1), pages 285-299.
    2. Sowell, Fallaw, 1992. "Maximum likelihood estimation of stationary univariate fractionally integrated time series models," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 165-188.
    3. Valderio A. Reisen, 1994. "ESTIMATION OF THE FRACTIONAL DIFFERENCE PARAMETER IN THE ARIMA(p, d, q) MODEL USING THE SMOOTHED PERIODOGRAM," Journal of Time Series Analysis, Wiley Blackwell, vol. 15(3), pages 335-350, May.
    4. Stanley, H.E & Buldyrev, S.V & Goldberger, A.L & Havlin, S & Peng, C.-K & Simons, M, 1999. "Scaling features of noncoding DNA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 273(1), pages 1-18.
    5. C. W. J. Granger & Roselyne Joyeux, 1980. "An Introduction To Long‐Memory Time Series Models And Fractional Differencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 15-29, January.
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    Citations

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    Cited by:

    1. Gao, Jie & Xu, Zhen-yuan & Zhang, Li-ting, 2009. "Approximating long-memory DNA sequences by short-memory process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(17), pages 3475-3485.
    2. Asgari, Ali & Si, Wujun & Yuan, Liang & Krishnan, Krishna & Wei, Wei, 2024. "Multivariable degradation modeling and life prediction using multivariate fractional Brownian motion," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    3. Marques, G.O.L.C., 2011. "Empirical aspects of the Whittle-based maximum likelihood method in jointly estimating seasonal and non-seasonal fractional integration parameters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(1), pages 8-17.
    4. Kembro, Jackelyn M. & Flesia, Ana Georgina & Gleiser, Raquel M. & Perillo, María A. & Marin, Raul H., 2013. "Assessment of long-range correlation in animal behavior time series: The temporal pattern of locomotor activity of Japanese quail (Coturnix coturnix) and mosquito larva (Culex quinquefasciatus)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6400-6413.
    5. N. Crato & R. R. Linhares & S. R.C. Lopes, 2011. "α-stable laws for noncoding regions in DNA sequences," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(2), pages 261-271, September.

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