Statistical inference based on Lindley record data

A. Asgharzadeh (), A. Fallah, M. Z. Raqab and R. Valiollahi
Additional contact information
A. Asgharzadeh: Faculty of Mathematical Sciences University of Mazandaran
A. Fallah: Payame Noor University
M. Z. Raqab: Kuwait University
R. Valiollahi: Semnan University

Statistical Papers, 2018, vol. 59, issue 2, No 15, 759-779

Abstract: Abstract Based on record statistics from Lindley distribution, we consider here the problem of estimating the model parameter and predicting the unobserved records. Frequentist and Bayesian analyses are discussed for making some inferences for the model parameter and prediction of unobserved records. Frequentist methods involving maximum likelihood estimation and moments based estimation and Bayesian sampling-based technique are applied for estimating the unknown shape parameter as well as predicting the future unobserved units. The corresponding point predictors and credible intervals of future record values based on an informative set of records can be developed. Real data analysis has been performed for illustrative purposes.

Keywords: Lindley distribution; Maximum likelihood estimation; Moments based estimate; Bayesian estimation and prediction; 62F10; 62F15; 62F25; 62E25 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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DOI: 10.1007/s00362-016-0788-1

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