We propose a Generalized Poisson-Pseudo Maximum Likelihood (G-PPML) estimator that relaxes the PPML estimator's assumption that the dependent variable's conditional variance is proportional to its conditional mean. Instead, we employ an iterated Generalized Method of Moments (iGMM) to estimate...

We develop a new class of distributions, namely, the odd power generalized Weibull-G powerseries (OPGW-GPS) class of distributions. We present some special classes of the proposeddistribution. Structural properties, have also been derived. We conducted a simulation studyto evaluate the...

In this article, the length-biased power hazard rate distribution has introduced and investi-gated several statistical properties. This distribution reports an extension of several prob-ability distributions, namely: exponential, Rayleigh, Weibull, and linear hazard rate. Theprocedure of maximum...

A Fibonacci-type probability distribution provides the probabilistic models for establishing stopping rules associated with the number of consecutive successes. It can be interpreted as a generalized version of a geometric distribution. In this article, after revisiting the Fibonacci-type...

The Uniformly Minimum Variance Unbiased (UMVU) and the Maximum Likelihood (ML) estimations of R = P(X ≤ Y) and the associated variance are considered for independent discrete random variables X and Y. Assuming a discrete uniform distribution for X and the distribution of Y as a member of the...

In this paper, a new Poisson area-biased Ailamujia distribution has been formulated to analyse count data. It was created by combining two distributions: the Poisson and area-biased Ailamujia distributions, using the compounding technique. Several distributional properties of the formulated...

This study presents an approach to apply the maximum likelihood estimation (MLE) method to estimate the parameters in quantitative spatial economic models. The proposed method can be applied to any model in which the unique values of the error terms can be recovered from the observed data on the...

We propose a Generalized Poisson-Pseudo Maximum Likelihood (G-PPML) estimator that relaxes the PPML estimator’s assumption that the dependent variable’s conditional variance is proportional to its conditional mean. Instead, we employ an iterated Generalized Method of Moments (iGMM) to...