Estimating Predictive Inference for Responses from the Generalized Rayleigh Model based on Complete Sample

Authors

  • Hafiz M. R. Khan Department of Biostatistics, Robert Stempel College of Public Health & Social Work, Florida International University, 11200 S.W. 8th Street, Miami, FL 33199, USA.

Keywords:

Statistical inference, Generalized Rayleigh model, Likelihood function, Posterior density, Predictive inference

Abstract

In this paper, the likelihood function given a complete sample from the two-parameter generalized Rayleigh model is derived. By making use of the Bayesian framework, the posterior density function, the predictive density for a single future response, a bivariate future response, and several future responses are derived. A comparison of the predictive variability of the maximum likelihood estimates and some of its neighborhood estimates are provided. The predictive means, standard deviations, 95% highest predictive density intervals, and the shape characteristics for a single future response are determined. A real data set is utilized to illustrate the predictive results.

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How to Cite

Khan, H. M. R. (2015). Estimating Predictive Inference for Responses from the Generalized Rayleigh Model based on Complete Sample. Thailand Statistician, 10(1), 53–68. Retrieved from https://ph02.tci-thaijo.org/index.php/thaistat/article/view/34232

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Articles