Novel Extended One Parameter of 10 Mixture Gamma (NEG10) Distributions and Application

Abstract A new one parameter lifetime distribution named, ‘the novel extended 10-mixture gamma (NEG10) distribution’ for modeling lifetime data from engineering, has been proposed. The method of maximum likelihood has been discussed for estimating its parameter. The goodness of fit of the proposed distribution over one parameter Lindley, Sujatha, Amarendra, Devya, Shambhu, mixture 7 component gamma distribution, mixture 8 component gamma distribution and mixture 9 component gamma, and NEG10 distributions have been given with two real lifetime data sets. The maximum likelihood method will be employed to estimate the parameter values of the distributions used in this study. Additionally, graphical assessments (density-density plot) and numerical criteria (Akaike’s Information Criterion (AIC), -2*log likelihood) will be utilized to determine the best-fitting model. In most instances, the results obtained from graphical assessments were consistent but differed from the numerical criteria. The model with the lowest values of AIC and -2*log likelihood was selected as the best fit. Overall, the NEG10 distribution was identified as the most suitable model