A Short Review on Bayesian Estimation of a Common Coefficient of Variation from Inverse Gaussian Distributions
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Authors
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Murari Singh
Department of Statistical Sciences, University of Toronto, Toronto, ON M5G 1Z5, CANADA
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Yogendra P. Chaubey
Department of Mathematics and Statistics, University of Northern British Columbia, Prince George, BC V2N 4Z9, Canada
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Debaraj Sen
Department of Mathematics and Statistics, Concordia University, 1455 De Maisonneuve Blvd. W., Montre ́al, QC H3G 1M8, CANADA
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Ashutosh Sarker
International Center for Agricultural Research in the Dry Areas (ICARDA), New Delhi
Keywords:
Common coefficient of variation; Inverse gaussian distribution; Bayesian inference; Conjugate priors; Lentil trials.Abstract
The coefficient of variation (CV) has been used in different disciplines with varied purpose related to variation in quantitative measurements. Statistical properties of CV have been studied by various researchers. Recently, a paper by the authors featuring an investigation of the posterior distribution of a common CV for inverse Gaussian populations with priors obtained through some empirical fitting procedure was presented by YPC at the 2022 ISBA World Meeting, June 26-July 1, 2022, held in Montreal, Canada. Some of these results along with other current developments by the authors on the topic were also reviewed during an invited presentation by MS in the honor of Dr. Daroga Singh at the 73rd Annual Conference of ISAS Conference held at the Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, November 14-16, 2022. The purpose of this paper is to summarize and discuss three key papers on estimation and testing of CV from inverse Gaussian distribution focussed on – a common CV (from multiple populations under frequentist framework), CV for a single population with Bayesian framework and a common CV from multiple populations and Bayesian framework, reviewed at this conference.
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References
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