MODELING BREAST CANCER DATA USING A NOVEL THREE PARAMETER GUL ALPHA POWER EXPONENTIAL MODEL
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Keywords
Akaike Information Criterion, Bayesian Information Criterion, Anderson-Darling estimation, Cramér-von Mises estimation, data analysis, exponential distribution, mean residual life.
Abstract
Breast Cancer is a common type of cancer found in women. In this paper, we model breast cancer data using a new three parameter family of distribution, called the Three Parameter Gull Alpha Power Exponential (TP-GAPE) Distribution. The new distribution is more useful because it can correspond to various hazard rate functions, which are widely used in reliability investigations. With the help of the proposed model, data with rising, uni-modal, and modified uni-modal hazard rate functions can be analyzed. We determine the essential statistical and reliability properties of the suggested model. The goodness-of-fit criteria have been studied using two real-life data sets. The proposed model is compared to other current modifications of the exponential distribution with the aim of evaluating the model's efficacy using a variety of goodness of fit measures, including the Akaike Information Criterion, Bayesian Information Criterion, etc. These results suggest that the proposed model fits the cancer data as well as some other scientific data more precisely than any recently developed extensions of exponential distribution.
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Abdur Rehman
Department of Statistics, University of Peshawar
Alamgir
Department of Statistics, University of Peshawar
Sajjad Ahmad Khan
Department of Statistics, Islamia College Peshawar
Gul Karam Khan
Gajju Khan Medical College Swabi,
Muhammad Ilyas
Department of Statistics, University of Malakand, KP,
Sundas Hussain
Department of Statistics, Shaheed Benazir Bhutto Women University Peshawar,