Statistical inference based on Lindley record data

被引：0
|
作者：
A. Asgharzadeh
A. Fallah
M. Z. Raqab
R. Valiollahi
机构：
[1] Faculty of Mathematical Sciences University of Mazandaran,Department of Statistics
[2] Payame Noor University,Department of Statistics, Faculty of Mathematics
[3] Kuwait University,Department of Statistics & OR
[4] The University of Jordan,Department of Mathematics
[5] Semnan University,Faculty of Mathematics, Statistics and Computer Science
来源：
Statistical Papers | 2018年 / 59卷
关键词：
Lindley distribution; Maximum likelihood estimation; Moments based estimate; Bayesian estimation and prediction; 62F10; 62F15; 62F25; 62E25;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
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页码：759 / 779
页数：20
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