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Comparing estimation of the parameters of distribution of the root density of plants in the presence of outliers

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  • Mehdi Jabbari Nooghabi

Abstract

The root density of plants with depth follows exponential or the Lindley distribution in the presence of outliers generated from a uniform distribution. In this article, we estimate the parameters of the Lindley distribution in the presence of outliers generated from a uniform distribution based on the moment, maximum likelihood, least squares, weighted least squares, percentile, Cramer–von‐Mises, and Anderson–Darling methods and mixture estimator of moment and maximum likelihood. These methods of estimation are compared. Also, the estimators of the parameters of Lindley‐uniform contaminated distribution are compared with the corresponding estimators of exponential‐uniform contaminated distribution, which was presented by Dixit and Nasiri, Metron, 59(3–4), 187–198 (2001). Furthermore, an analysis of an actual example of the root length of plants is presented for illustrative purposes. It is concluded that the Lindley‐uniform contaminated distribution is more appropriate than the exponential‐uniform contaminated distribution to model the root density of plants.

Suggested Citation

  • Mehdi Jabbari Nooghabi, 2021. "Comparing estimation of the parameters of distribution of the root density of plants in the presence of outliers," Environmetrics, John Wiley & Sons, Ltd., vol. 32(5), August.
    • Handle: RePEc:wly:envmet:v:32:y:2021:i:5:n:e2676
    DOI: 10.1002/env.2676
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    References listed on IDEAS

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    1. M. E. Ghitany & D. K. Al-Mutairi, 2008. "Size-biased Poisson-Lindley distribution and its application," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 299-311.
    2. Ulhas J. Dixit & Parviz F. Nasiri, 2001. "Estimation of parameters of the exponential distribution in the presence of outliers generated from uniform distribution," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3-4), pages 187-198.
    3. M. Jabbari Nooghabi & E. Khaleghpanah Nooghabi, 2016. "On entropy of a Pareto distribution in the presence of outliers," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(17), pages 5234-5250, September.
    4. Okhli, Kheirolah & Jabbari Nooghabi, Mehdi, 2021. "On the contaminated exponential distribution: A theoretical Bayesian approach for modeling positive-valued insurance claim data with outliers," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    5. Ghitany, M.E. & Al-Mutairi, D.K. & Nadarajah, S., 2008. "Zero-truncated Poisson–Lindley distribution and its application," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 279-287.
    6. Ghitany, M.E. & Atieh, B. & Nadarajah, S., 2008. "Lindley distribution and its application," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(4), pages 493-506.
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