Abstract
As data types evolved many problems related to the representation and modeling of this data began to emerge creating a need to find solutions. Over the past few years many methods have been proposed to generate new families of continuous distributions and study them in various applications including medicine engineering physics economics finance biology and environmental studies and the solution is to extend these distributions. In recent years many methods have been proposed to create new distributions. We generate a new of family distributions named PF- LD . Some properties of our distribution are introduced. Such as rth moment function, reliability function, hazard rate function, Shannon entropy function and stress-strength models. A simulation study was carried out for this compare the performance of different estimates from PF-LD. We create random variable from PF-LD for different sample sizes and different parameters values. The simulation study was repeated every (1000N) with a sample sizes (n=30,60,160). And numerical simulations can be performed for different parameter values by solving nonlinear equations and calculating MSE for parameter estimation. The results we obtained using the Matlab code observed a lower MSE when the default parameter values were small. (β=0.5, λ=0.5, α =0.5 ). for all sample size . Based on the knowledge and information obtained from this research, we recommend, applying the proposed distribution to real data.
Published Version
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