Statistical Analysis and Model Validation of Gompertz Model on different Real Data Sets for Reliability Modelling

A very basic problem in reliability modeling is to obtain information about the form of the population from which the sample is drawn. Goodness of fit test is employed on different real data sets to determine how well the observed sample data "fits" on proposed model for reliability analysis. In this paper, we obtain the tables and graphs of critical values of Kolmogorov-Smirnov (KS) test, and Q-Q test for Gompertz model with two unknown parameters. These plots are used to investigate whether an assumed model adequately fits a set of data and we present power comparison between Computation of MLE using Newton‐Raphson method and p-value with its corresponding D-value obtaining by KS-Test Q-Q test for model validation to obtain feasible real data sets which are most suitable for parameter estimation of Gompertz model. For this analysis, we used different tools which are developed in R language and environment for model analysis, model validation and estimation of parameters using method of maximum likelihood.