MODELING BLADDER CANCER PATIENTS DATA THROUGH AN SIA LOGSYMMETRIC DISTRIBUTION FOR ACHIEVING BETTER FIT

Abstract

Demography is the study of facts and figures regarding human populations such as births, deaths, incidence of disease, etc. which illustrate the changing structure of populations of various countries of the world. In this paper, we consider a data-set pertaining to remission times of bladder cancer patients which has already been modeled by a few researchers using various probability distributions. With a view to obtaining an even better fit than those achieved so far, we apply one of the SIA log-symmetric distributions to this data-set utilizing the self inversion property for parameter-estimation. Evidently, the better the fit, the more accurate will be the estimation of probabilities of early remission, an information necessary for oncologists and cancer-care providers.