Transmuted Power Function Distribution : A more flexible Distribution

Abstract

Double-bounded data appears in many applications related to engineering, economics, hydrology, social and behavioral sciences. To model the double-bounded data the Power function distribution is an obvious choice. To enhance its applicability, we proposed transmuted Power function distribution in this study. The new distribution relatively more flexible and performs better in reliability and meteorological data analysis than the parent distribution. Its various mathematical properties are derived such as mean, mode, median, variance, quantile function, reliability function and hazard function. The order statistics and generalized TL-moments with its special cases L-, TL-, LL- and LH-moments are also explored. Parameters estimation is approached through method of maximum likelihood estimation and to evaluate their performance a simulation study has been carried out. Finally, the transmuted and parent distributions is illustrated and compared through two real data sets.