Abstract
A new four-parameter lifetime distribution named as the power Lomax Poisson is introduced and studied. The subject distribution is obtained by combining the power Lomax and Poisson distributions. Structural properties of the power Lomax Poisson model are implemented. Estimation of the model parameters are performed using the maximum likelihood, least squares and weighted least squares techniques. An intensive simulation study is performed for evaluating the performance of different estimators based on their relative biases, standard errors and mean square errors. Eventually, the superiority of the new compounding distribution over some existing distribution is illustrated by means of two real data sets. The results showed the fact that, the suggested model can produce better fits than some well-known distributions.
Highlights
Lomax (1954) suggested an important model for lifetime analysis called Lomax (Pareto type II) distribution
Its widely applied in some areas, such as, analysis of income and wealth data, modeling business failure data, biological sciences, model firm size and queuing problems, reliability modeling and life testing (see Harris (1968), Atkinson and Harrison (1978), Holland et al (2006), Corbellini et al (2007), Hassan and Al-Ghamdi (2009) and Hassan et al (2016), respectively
For the second data, the power Lomax Poisson (PLP) distribution is compared with Weibull Lomax (WL), Kumuerswmay Lomax (KL), beta Lomax (BL), exponentiated Lomax (EL) and L distributions Example 6.1: The first data set represents 84 observations of failure time for particular windshield model given in Table 16.11 of Murthy et al (2004)
Summary
Lomax (1954) suggested an important model for lifetime analysis called Lomax (Pareto type II) distribution. Adamidis and Loukas (1998) proposed the two-parameter exponential-geometric distribution with decreasing failure rate. Chahkandi and Ganjali (2009) proposed the exponential power series family of distributions with decreasing failure rate which contains as special cases the exponential Poisson, exponential geometric and exponential logarithmic distributions. A three-parameter Weibull power series distribution with decreasing, increasing, upside-down bathtub failure rate functions has been introduced by Morais and Barreto-Souza (2011). The generalized exponential power series distributions have been proposed by Mahmoudi and Jafari (2012). Alkarni (2016) introduced generalized extended Weibull power series class. Sagor (2014), Al-Zahrani (2015), and Hassan and Abd-Alla (2017) have been proposed, respectively, Lomax Poisson, exponentiated Lomax Poisson, Lomax-Logarithmic, extended.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
