Bayesian Analysis of Topp-Leone Generalized Exponential Distribution
The Topp-Leone distribution was introduced by Topp-Leone in 1955. In this paper, an attempt has been made to fit Topp-Leone Generalized Exponential distribution. Since, Topp-Leone distribution contains only one parameter and its support set is restricted to (0,1), because of this, in most practical situations it is not a better fit for the lifetime modelling. So an extension of this distribution is required. A Bayesian approach has been adopted to fit this model as survival model. A real survival data set is used to illustrate. Implementation is done using R and JAGS and appropriate illustrations are made. R and JAGS codes have been provided to implement censoring mechanism using both optimization and simulation tools.
Collet, D. (2003). Modelling Survival Data in Medical Research, second
edition. Chapman & Hall, London.
Gelman, A. and Hill, J. (2007). Data Analysis Using Regression
and Multilevel/Hierarchical Models. Cambridge University Press, New
Gelman, A. (2008). Scaling Regression Inputs by Dividing by Two Standard Deviations. Statistics in Medicine, 27: 28652873.
Ibrahim, J. G., Chen, M.H. and Sinha, D. (2001). Bayesian Survival
Khan, N., Akhtar, M. T. and Khan, A. A. (2016). A Bayesian Approach
to Survival Analysis of Inverse Gaussian Model with Laplace Approxi-
mation.International Journal of Statistics and Applications, 6(6): 391-
Mosteller, F. and Wallace, D. L. (1964). Inference and Disputed Au-
thorship: The Federalist. Reading: Addison-Wesley.
Nocedal, J., and Wright, S. J. (1999). Numerical Optimization.
R Core Team (2015). R: A Language and Environment for Statistical
Computing. R Foundation for Statistical Computing, Vienna, Austria,
ISBN 3-900051-07-0, URL http://www.R-project.org.
Statisticat LLC (2015). LaplacesDemon: Complete environment for
Bayesian inference. R package version 3.2.0, http://www.bayesian-
Sangsanit, Y. and Bodhisuwan, W. (2016). The Topp-Leone genera-
tors of distributions: properties and inference. Songklanakarin J. Sci.
Tanner, M. A. (1996). Tools for Statistical Inference. Springer-Verlag,
Tierney, L. and Kadane, J. B. (1986). Accurate approximations for
posterior moments and marginal densities. Journal of the American
Statistical Association 81, 82-86.
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