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The Gamma Kumaraswamy-G family of distributions: theory, inference and applications

100%
Arshad R. M. I., Tahir M. H., Chesneau C., Jamal F.
Statistics in Transition new series
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2020
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vol. 21
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issue 5
17-40
EN
In this paper, we introduce a new family of univariate continuous distributions called the Gamma Kumaraswamy-generated family of distributions. Most of its properties are studied in detail, including skewness, kurtosis, analytical comportments of the main functions, moments, stochastic ordering and order statistics. The next part of the paper focuses on a particular member of the family with four parameters, called the gamma Kumaraswamy exponential distribution. Among its advantages, the following should be mentioned: the corresponding probability density function can have symmetrical, left-skewed, right-skewed and reversed-J shapes, while the corresponding hazard rate function can have (nearly) constant, increasing, decreasing, upside-down bathtub, and bathtub shapes. Subsequently, the inference on the gamma Kumaraswamy exponential model is performed. The method of maximum likelihood is applied to estimate the model parameters. In order to demonstrate the importance of the new model, analyses on two practical data sets were carried out. The results proved more favourable for the studied model than for any of the other eight competitive models.
2
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A Two-Parameter Lindley Distribution

39%
Shanker R., Mishra A.
Statistics in Transition new series
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2013
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vol. 14
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issue 1
45-56
EN
A two-parameter Lindley distribution, of which the Lindley distribution (LD) is a particular case, has been introduced. Its moments, failure rate function, mean residual life function and stochastic orderings have been discussed. The maximum likelihood method and the method of moments have been discussed for estimating its parameters. The distribution has been fitted to some data-sets to test its goodness of fit.
3
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A New Quasi Sujatha Distribution

32%
Shanker R., Shukla K. K.
Statistics in Transition new series
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2020
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vol. 21
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issue 3
53-71
EN
The aim of this paper is to introduce a new quasi Sujatha distribution (NQSD), of which the following are particular cases: the Sujatha distribution devised by Shanker (2016 a), the sizebiased Lindley distribution, and the exponential distribution. Its moments and momentsbased measures are derived and discussed. Statistical properties, including the hazard rate and mean residual life functions, stochastic ordering, mean deviations, Bonferroni and Lorenz curves and stress-strength reliability are also analysed. The method of moments and the method of maximum likelihood estimations is discussed for estimating parameters of the proposed distribution. A numerical example is presented to test its goodness of fit, which is then compared with other one-parameter and two-parameter lifetime distributions.
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