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Different Parameter Estimation Methods for Exponential Geometric Distribution and Its Applications in Lifetime Data Analysis

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  • Feyza Günay

    (Graduate School of Natural and Applied Sciences, Ankara University, Turkey)

  • Mehmet Yilmaz

    (Graduate School of Natural and Applied Sciences, Ankara University, Turkey)

Abstract

The new compound distributions which are started to be used with the study of Adamidis, et al. [1] still take place in recent studies. Exponential Geometric distribution, introduced by them, is a flexible distribution for modeling the lifetime data sets. They have used maximum likelihood method with expectation-maximization algorithm to estimate unknown parameters. In this paper, we use maximum likelihood and also least squares, weighted least squares, maximum product of spacings and l-moments methods to estimate the unknown parameters of exponential geometric distribution family. Then we compare the efficiency of these estimators via a simulation study for different sample sizes and parameter settings.

Suggested Citation

  • Feyza Günay & Mehmet Yilmaz, 2018. "Different Parameter Estimation Methods for Exponential Geometric Distribution and Its Applications in Lifetime Data Analysis," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 8(2), pages 36-43, September.
    • Handle: RePEc:adp:jbboaj:v:8:y:2018:i:2:p:36-43
    DOI: 10.19080/BBOAJ.2018.08.555735
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    References listed on IDEAS

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    1. Cancho, Vicente G. & Louzada-Neto, Franscisco & Barriga, Gladys D.C., 2011. "The Poisson-exponential lifetime distribution," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 677-686, January.
    2. Adamidis, K. & Loukas, S., 1998. "A lifetime distribution with decreasing failure rate," Statistics & Probability Letters, Elsevier, vol. 39(1), pages 35-42, July.
    3. Adamidis, Konstantinos & Dimitrakopoulou, Theodora & Loukas, Sotirios, 2005. "On an extension of the exponential-geometric distribution," Statistics & Probability Letters, Elsevier, vol. 73(3), pages 259-269, July.
    4. Barreto-Souza, Wagner & Cribari-Neto, Francisco, 2009. "A generalization of the exponential-Poisson distribution," Statistics & Probability Letters, Elsevier, vol. 79(24), pages 2493-2500, December.
    5. Louzada, Francisco & Roman, Mari & Cancho, Vicente G., 2011. "The complementary exponential geometric distribution: Model, properties, and a comparison with its counterpart," Computational Statistics & Data Analysis, Elsevier, vol. 55(8), pages 2516-2524, August.
    6. Kus, Coskun, 2007. "A new lifetime distribution," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4497-4509, May.
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