The Odd Power Lindley Generator of Probability Distributions: Properties, Characterizations and Regression Modeling

Abstract

In this study, a new flexible family of distributions is proposed with its statistical properties as well as some useful characterizations. The maximum likelihood method is used to estimate the unknown model parameters by means of two simulation studies. A new regression model is proposed based on a special member of the proposed family called, the log odd power Lindley Weibull distribution. Residual analysis is conducted to evaluate the model assumptions. Four applications to real data sets are given to demonstrate the usefulness of the proposed model.

A New Flexible Three-Parameter Model: Properties, Clayton Copula, and Modeling Real Data

“…The second data set (0.1, 0.33, 0.44, 0.56, 0.59, 0.72, 0.74, 0.77, 0.92, 0.93, 0.96, 1, 1, 1.02, 1.05, 1.07, 07, 1.08, 1.08, 1.08, 1.09, 1.12, 1.13, 1.15, 1.16, 1.2, 1.21, 1.22, 1.22, 1.24, 1.3, 1.34, 1.36, 1.39, 1.44, 1.46, 1.53, 1.59, 1.6, 1.63, 1.63, 1.68, 1.71, 1.72, 1.76, 1.83, 1.95, 1.96, 1.97 (1960). Many other real data sets related to failure times can be found in [13][14][15][16][17][18][19][20]. Figure 3 gives the total time test (TTT) plots.…”

A new three parameter Fréchet model with mathematical properties and applications

“…This section presents two applications of the new distribution using real data sets. We shall compare the fit of the new distribution with the Poisson Burr X Fr [19], Abd El-Bar and Ragab [27], Hamedani et al [28], Ahsanul Haq et al [29], Basheer [30], Korkmaz et al [31], Mukhtar [32], Alizadeh et al [33,34], Yousof et al [35][36][37] and Korkmaz et al [38]. In order to compare the distributions, we consider the following criteria: the −2 (α,β,λ) (Maximized…”

A New Parametric Life Family of Distributions: Properties, Copula and Modeling Failure and Service Times

“…Table 5 gives the MaxLEs and StErs for service time data, and Table 6 gives the −ˆ and GOFs statistics for the service time data. Based on Tables 4 and 6 It is worth mentioning that the presented class of stochastic distributions can have also an important utilization in the insurance industry, risks, reliability, medicine and engineering (see [36][37][38][39][40][41][42][43][44][45][46][47]).…”