New Odoma Distribution with Application to Cancer Data

Abstract

Objective: To find appropriate model more flexible than classical models for fitting the survival data in health research especially in cancer blood (Leukemia) studies by introducing some additional parameters to the basic models. Methods: Based on the Alpha Power transformation technique and using Two-Parameter Odoma distribution, the new distribution called the Alpha Power Two-Parameter Odoma distribution is introduced and studied. The maximum likelihood estimation procedure is employed to estimate the unknown parameters. A simulation study is carried out to evaluate the performance of the maximum likelihood estimators. Finding: Common statistical properties such as quantile function, rth moments, moment generating function, characteristic function, incomplete moments, entropy and order statistics are derived. The practical importance of the proposed model is illustrated by using goodness-of-fit criterias based on real data set. Novelty: The APTPO distribution is the most appropriate model for fitting survival data of cancer studies comparing with other competitive distributions.

Power XShanker Distribution: Properties, Estimation, and Applications

“…In reality, such data are common in stock market records, biomedical events, the tensile strength of an engineering material, etc. Some of the existing articles on powertransformed Lindley-class of distributions are [1][2][3][4][5][6][7][8][9][10][11][12]. The gap in the literature is that none of these power-transformed Lindleyclass creations has harnessed the estimation of parameters using the Bayesian approach.…”