Article | 15-March-2019
In this study, we introduce a new model called the Extended Exponentiated Power Lindley distribution which extends the Lindley distribution and has increasing, bathtub and upside down shapes for the hazard rate function. It also includes the power Lindley distribution as a special case. Several statistical properties of the distribution are explored, such as the density, hazard rate, survival, quantile functions, and moments. Estimation using the maximum likelihood method and inference on a
V. Ranjbar,
M. Alizadeh,
G. G. Hademani
Statistics in Transition New Series, Volume 19 , ISSUE 4, 621–643
Research Article | 01-June-2020
In recent years, modifications of the classical Lindley distribution have been considered by many authors. In this paper, we introduce a new generalization of the Lindley distribution based on a mixture of exponential and gamma distributions with different mixing proportions and compare its performance with its sub-models. The new distribution accommodates the classical Lindley, Quasi Lindley, Two-parameter Lindley, Shanker, Lindley distribution with location parameter, and Three-parameter
Ramajeyam Tharshan,
Pushpakanthie Wijekoon
Statistics in Transition New Series, Volume 21 , ISSUE 2, 89–117
Article | 15-March-2019
In this article, we have derived suitable U-statistics from a sample of any size exceeding a specified integer to estimate the location and scale parameters of Lindley distribution without the evaluation of means, variances and co-variances of order statistics of an equivalent sample size arising from the corresponding standard form of distribution. The exact variances of the estimators have been also obtained.
M. R. Irshad,
R. Maya
Statistics in Transition New Series, Volume 19 , ISSUE 4, 597–620
Research Article | 24-August-2017
In this paper a three-parameter weighted Lindley distribution, including Lindley distribution introduced by Lindley (1958), a two-parameter gamma distribution, a two-parameter weighted Lindley distribution introduced by Ghitany et al. (2011) and exponential distribution as special cases, has been suggested for modelling lifetime data from engineering and biomedical sciences. The structural properties of the distribution including moments, coefficient of variation, skewness, kurtosis and index
Rama Shanker,
Kamlesh Kumar Shukla,
Amarendra Mishra
Statistics in Transition New Series, Volume 18 , ISSUE 2, 291–310
Article | 15-March-2019
Halim Zeghdoudi,
Lazri Nouara,
Djabrane Yahia
Statistics in Transition New Series, Volume 19 , ISSUE 4, 671–692
Research Article | 27-May-2018
real lifetime data from engineering, and its goodness of fit shows better fit over two-parameter power Akash distribution (PAD), twoparameter power Lindley distribution (PLD) and one-parameter Ishita, Akash, Lindley and exponential distributions.
Kamlesh Kumar Shukla,
Rama Shanker
Statistics in Transition New Series, Volume 19 , ISSUE 1, 135–148
Article | 20-September-2020
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
Rama Shanker,
Kamlesh Kumar Shukla
Statistics in Transition New Series, Volume 21 , ISSUE 3, 53–71
Research Article | 27-May-2018
Lahsen Bouchahed,
Halim Zeghdoudi
Statistics in Transition New Series, Volume 19 , ISSUE 1, 61–74
Article | 06-July-2017
Rama Shanker
Statistics in Transition New Series, Volume 17 , ISSUE 3, 391–410