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In order to improve the already existing models that are used extensively inbio sciences and applied sciences research, a new class of Weighted Powerfunction distribution (WPFD) has been proposed with its various properties anddifferent modifications to be more applicable in real life. We have providedthe mathematical derivations for the new distribution including moments,incomplete moments, conditional moments, inverse moments, mean residualfunction, vitality function, order statistics, mills ratio, informationfunction, Shannon entropy, Bonferroni and Lorenz curves and quantile function.We have also characterized the WPFD, based on doubly truncated mean. The aim ofthe study is to increase the application of the Power function distribution.The main feature of the proposed distribution is that there is no induction ofparameters as compare to the other generalization of the distributions, whichare complexed having many parameters. We have used R programming to estimatethe parameters of the new class of WPFD using Maximum Likelihood Method (MLM),Percentile Estimators (P.E) and their modified estimators. After analyzing thedata, we conclude that the proposed model WPFD performs better in the data setswhile compared to different competitor models.

Asymmetry approach to study for chemotherapy treatment and devices  failure times data using modified Power function distribution with some  modified estimators