Bayesian Predictive Inference for Some Linear Models under Student-t Errors
(Sprache: Englisch)
In real life often we need to make inferences about thebehaviour of the unobserved responses for a model based on theobserved responses from the model. Regression models with normalerrors are commonly considered in prediction problems. However,when the...
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In real life often we need to make inferences about thebehaviour of the unobserved responses for a model based on theobserved responses from the model. Regression models with normalerrors are commonly considered in prediction problems. However,when the underlying distributions have heavier tails, the normalerrors assumption fails to allow sufficient probability in the tailareas to make allowance for any extreme value or outliers. As well,it cannot deal with the uncorrelated but not independentobservations which are common in time series and econometricstudies. In such situations, the Student-t errors assumption isappropriate. Traditionally, a number of statistical methods such asthe classical, structural distribution and structural relationsapproaches can lead to prediction distributions, the Bayesianapproach is more sound in statistical theory. This book, therefore,deals with the derivation problems of prediction distributions forsome widely used linear models having Student-t errors under theBayesian approach. Results reveal that our models are robust andthe Bayesian approach is competitive with traditional methods. Inperturbation analysis, process control, optimization,classification, discordancy testing, interim analysis, speechrecognition, online environmental learning and sampling curtailmentstudies predictive inferences are successfully used.
Autoren-Porträt von Azizur Rahman
Azizur Rahman is a PhD candidate and research assistant in NATSEM at the University of Canberra. He has recently completed a Master of Philosophy (with High Distinction) in Statistics from the University of Southern Queensland, Australia. He also has a B.Sc. (Honours) and M.Sc. (with Thesis) degrees in Statistics from the University of Chittagong in Bangladesh. His work experience includes tutoring at university and research in theoretical and applied statistics, demography, small area estimation and microsimulation modelling, and has written widely on these issues.
Bibliographische Angaben
- Autor: Azizur Rahman
- 2008, 88 Seiten, Maße: 15,1 x 22,4 cm, Kartoniert (TB), Englisch
- Verlag: VDM Verlag Dr. Müller
- ISBN-10: 3639040864
- ISBN-13: 9783639040869
Sprache:
Englisch
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