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Bayesian Analysis of Extreme Values Using Splines in Generalized Mixed Model
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| Behzad Mahmoudian *, Mousa Golalizadeh |
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Abstract: (21110 Views) |
| Modeling of extreme responses in presence nonlinear,
temporal, spatial and interaction effects can be accomplished with
mixed models. In addition, smoothing spline through mixed model and
Bayesian approach together provide convenient framework for
inference of extreme values. In this article, by representing as a mixed model,
smoothing spline is used to assess nonlinear covariate effect on extreme values.
For this reason, we assume that extreme responses given covariates and random effects are
independent with generalized extreme value distribution.
Then by using MCMC techniques in Bayesian framework, location parameter of distribution
is estimated as a smooth function of covariates. Finally, the proposed model is employed to
model the extreme values of ozone data. |
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| Keywords: Extreme Values, Generalized Extreme Value Distribution, Smoothing Spline, Bayesian Approach, Block minimas, Ozone data. |
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Full-Text [PDF 472 kb]
(3031 Downloads)
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Type of Study: Research |
Subject:
Spatial Statistics
Received: 2011/07/4 | Accepted: 2013/08/13 | Published: 2020/02/18
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