Research Article | 04-September-2019
Vivek Verma,
Dilip C. Nath
Statistics in Transition New Series, Volume 20 , ISSUE 3, 1–29
Article | 06-July-2017
In this paper a new one-parameter lifetime distribution named “Sujatha Distribution” with an increasing hazard rate for modelling lifetime data has been suggested. Its first four moments about origin and moments about mean have been obtained and expressions for coefficient of variation, skewness, kurtosis and index of dispersion have been given. Various mathematical and statistical properties of the proposed distribution including its hazard rate function, mean residual life function
Rama Shanker
Statistics in Transition New Series, Volume 17 , ISSUE 3, 391–410
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 | 20-December-2020
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
Rana Muhammad Imran Arshad,
Muhammad Hussain Tahir,
Christophe Chesneau,
Farrukh Jamal
Statistics in Transition New Series, Volume 21 , ISSUE 5, 17–40
Research Article | 08-December-2021
residual function, median, moment gen erating function, skewness, kurtosis, coefficient of variation, and index of dispersion, were derived. The estimation of the proposed distribution parameter was based on the maximum likelihood estimation method. The real-life applications of the distribution were illustrated using two real lifetime negatively and positively skewed data sets. The new distribution pro vides a better fit than the Pranav, exponential, and Lindley distributions for the data sets. The
Friday Ikechukwu Agu,
Joseph Thomas Eghwerido
Statistics in Transition New Series, Volume 22 , ISSUE 4, 59–76