This paper interest to estimation the unknown parameters for generalized Rayleigh distribution model based on censored samples of singly type one . In this paper the probability density function for generalized Rayleigh is defined with its properties . The maximum likelihood estimator method is used to derive the point estimation for all unknown parameters based on iterative method , as Newton – Raphson method , then derive confidence interval estimation which based on Fisher information matrix . Finally , testing whether the current model ( GRD ) fits to a set of real data , then compute the survival function and hazard function for this real data.

This paper introduces and developed a new lifetime distribution known as inverse exponential Rayleigh distribution (IERD). The new two-scale parameters generalized distribution was studies with its distribution and density functions, besides that the basic properties such as survival, hazard, cumulative hazard, quantile function, skewness, and Kurtosis functions were established and derived. To estimate the model parameters, maximum likelihood, and rank set sampling estimation methods were applied with real-life data.

The main aim of this paper is to introduce a new two-parameter distribution called the inverse exponential Rayleigh distribution (IERD) with the investigated of its statistical properties. We introduce some mathematical complexity of statistical properties such as the moment function, moment generating function, factorial moments generating function, quantity function, skewness, and Kurtosis. We utilize Taylor series expansion to obtain these statistical properties. The process establishes the new distribution relied mainly on the survival functions of both the exponential and Rayleigh distributions. For the application, real data were applied to compare the new distribution with some other distributions using the Akaike information criteri

This paper demonstrates the construction of a modern generalized Exponential Rayleigh distribution by merging two distributions with a single parameter. The "New generalized Exponential-Rayleigh distribution" specifies joining the Reliability function of exponential pdf with the Reliability function of Rayleigh pdf, and then adding a shape parameter for this distribution. Finally, the mathematical and statistical characteristics of such a distribution are accomplished