Ensemble Bayesian model averaging using Markov Chain Monte Carlo sampling
نویسندگان
چکیده
منابع مشابه
Ensemble Bayesian model averaging using Markov Chain Monte Carlo sampling
Bayesian model averaging (BMA) has recently been proposed as a statistical method to calibrate forecast ensembles from numerical weather models. Successful implementation of BMA however, requires accurate estimates of the weights and variances of the individual competing models in the ensemble. In their seminal paper (Raftery et al. Mon Weather Rev 133:1155–1174, 2005) has recommended the Expec...
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A major limitation towards more widespread implementation of Bayesian approaches is that obtaining the posterior distribution often requires the integration of high-dimensional functions. This can be computationally very difficult, but several approaches short of direct integration have been proposed (reviewed by Smith 1991, Evans and Swartz 1995, Tanner 1996). We focus here on Markov Chain Mon...
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A major limitation towards more widespread implementation of Bayesian approaches is that obtaining the posterior distribution often requires the integration of high-dimensional functions. This can be computationally very difficult, but several approaches short of direct integration have been proposed (reviewed by Smith 1991, Evans and Swartz 1995, Tanner 1996). We focus here on Markov Chain Mon...
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ژورنال
عنوان ژورنال: Environmental Fluid Mechanics
سال: 2008
ISSN: 1567-7419,1573-1510
DOI: 10.1007/s10652-008-9106-3