Survival Function Estimation based on Neutrosophic two-parameter XLindley distribution

Abstract

The probability distribution is of paramount importance in probability theory as it abounds in application across most disciplines comprising science. It is reported to be used preferentially for actuarial studies on insurance and finance, in the medical field, agriculture, demography and econometric analyses. The focus of the current research work is to introduce a novel extension termed as the neutrosophic two-parameter XLindley distribution (NTPXL). Many mathematical characteristics that model life survival have been developed and studied, involving survival and hazard functions, moment-generating functions and other tests of average, variance, and standard deviation, skewness and kurtosis. Monte Carlo method has been applied to investigate the effectiveness of the NTPXL distribution estimate. The results of the simulation conducted for this study show that the task of estimating with satisfactory accuracy is possible if the sample size is large enough. The actuality of premature infant staying time data has been used to explain the exact way through which the elaborated NTPXL distribution should be applied. On the application aspects, it has been shown in the subsequent sections that the NTPXL distribution is versatile because it can handle classical data as well as data that comprises uncertainties, ambiguity or imprecision.