Chris-Jerry Distribution and Its Applications

Abstract

In this paper, a new one-parameter distribution named Chris-Jerry is suggested from two component mixture of Exponential (\(\theta\)) distribution and Gamma(3; \(\theta\)) distribution with mixing proportion \(p=\frac{\theta}{\theta + 2}\) having a flexibility advantage in modeling lifetime data. The statistical properties are discussed and the maximum likelihood estimation procedure is used to obtain the parameter estimate. The Convolution of the product of Pareto random variable with the proposed Chris-Jerry distributed random variable is explored with its marginal density derived. To illustrate the usefulness, three sets of lifetime data are employed and LL, AIC, BIC and K-S statistics are obtained for Exponential, Ishita, Akash, Rama, Pranav, Rani, Lindley, Sujatha, Aradhana, Shanker and XGamma and the Chris-Jerry distributions.

Inference on the Parameters of Zubair-Exponential Distribution with Application to Survival Times of Guinea Pigs

“…The basis of MCMC algorithms is the concept of a discrete-time evolving Markov chain. As a stochastic process, a Markov chain φ (0) , φ (1) , φ (2) , . .…”

“…To achieve a better fit, economy of parameter, flexibility and tractability of model, various authors have explored avenues of providing compact distributions that model lifetime data. Among them are Zubair [1], Onyekwere and Obulezi [2], Onyekwere et al [3]. Some authors have further studied various classical methods of estimation.…”

Optimal Estimation of Power Chris-Jerry DistributionParameters Using Ranked Set Sampling Design withApplication

“…In particular, it has been applied to predicting stress-strength reliability by analyzing large amounts of actual data. Using the similar idea of Lindley distribution, other probability distributions have been suggested, such as Akash distribution [31], Sujatha distribution [32], Aradhana distribution [33], xgamma distribution [34], Ishita distribution [35], and Chris-Jerry distribution (C-JD) [36], among others. Ezeilo et al [37] proposed a new recent more flexible lifetime model with two-parameter, called the power C-JD (PC-JD).…”

Simulation Study of the Bayesian and Non-Bayesian Estimation of a new Lifetime Distribution Parameters with Increasing Hazard Rate

“…Chris-Jerry distribution credit to Onyekwere and Obulezi [1] is a one-parameter life time distribution that is gaining attention in statistical literature. This is because it fits variety of data sets better than many competing distributions such as Lindley distribution [2], Exponential distribution [3], Akash distribution [4], Aradhana distribution [5], Sujatha distribution [6], Ishita distribution [7], XGamma distribution [8], Rama distribution [9], Shanker distribution [12], Rani distribution [10] and Pranav distribution [11].…”

“…Kumaraswamy Chris-Jerry distrbution by Obulezi et al [14], Zubair-Exponential distribution [15], Exponentiated Power Lindley-Logarithmic distribution( [16], [17]), Power size biased Chris-Jerry distribution [18], a new modified Lindley distribution by Chesneau [19], weibull distribution with estimable shift parameter by Onuoha et al [20] and Marshall-Olkin Chris-Jerry distribution [21].…”