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              <text>A Discrete Kumaraswamy Marshall-Olkin Exponential Distribution</text>
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              <text>Discrete distributions; Exponential distribution; Generalized family; Geometric distribution; Marshall-olkin extended distribution; Maximum likelihood estimation</text>
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              <text>Finding new families of distributions has become a popular tool in statistical research. In this article, we introduce a new flexible four-parameter discrete model based on the Marshall-Olkin approach, namely, the discrete Kumaraswamy MarshallOlkin exponential distribution. The proposed distribution can be viewed as another generalization of the geometric distribution and enfolds some important distributions as special cases. Some properties of the new distribution are derived. The model parameters are estimated by the maximum likelihood method, with validation through a complete simulation study. The usefulness of the new model is illustrated via counttype real data sets.  2022. Journal of the Iranian Statistical Society. All Rights Reserved.</text>
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              <text>Gillariose J.; Tomy L.; Jamal F.; Chesneau C.</text>
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              <text>Journal of the Iranian Statistical Society, Vol-20, No. 2, pp. 129-152.</text>
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              <text>Iranian Statistical Society</text>
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              <text>2022-01-01</text>
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              <text>&lt;a href="https://doi.org/10.52547/jirss.20.2.129" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.52547/jirss.20.2.129&lt;/a&gt;
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              <text>All Open Access; Gold Open Access</text>
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              <text>ISSN: 17264057</text>
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              <text>English</text>
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              <text>Gillariose J., Department of Statistics, CHRIST (Deemed to be University), Karnataka, Hosur Road, Bangalore, 560029, India; Tomy L., Department of Statistics, Deva Matha College, Kerala, Kuravilangad, 686633, India; Jamal F., Department of Statistics, The Islamia University of Bahawalpur, Punjab, 63100, Pakistan; Chesneau C., Universitde Caen, LMNO, Campus II, Science 3, Caen, 14032, France</text>
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