A new generalization of the gamma distribution with application to negatively skewed survival data |
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Authors: | Sophia D. Waymyers Sanku Dey Hrishikesh Chakraborty |
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Affiliation: | 1. Department of Mathematics, Francis Marion University, Florence, SC;2. Department of Statistics, St. Anthony’s College, Shillong, Meghalaya, India;3. Duke Clinical Research Institute, Duke University, Durham, NC |
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Abstract: | We propose a three-parameter distribution referred to as the reflected- shifted-truncated gamma (RSTG) distribution to model negatively skewed data. Various properties of the proposed distribution are derived. The estimation of the model parameters is approached by maximum likelihood methods and the observed information matrix is derived. Monte Carlo simulations are performed to compare the performances of the proposed methods of estimation for both small and large samples. Using information theoretic criteria, we compare the RSTG distribution to the exponential, generalized F, generalized gamma, Gompertz, log-logistic, lognormal, Rayleigh, and Weibull distributions in three negatively skewed real datasets. |
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Keywords: | Gamma distribution Negatively skewed data Survival analysis |
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