Showing 1 - 10 of 94
Adaptive Polar Sampling (APS) is proposed as a Markov chain Monte Carlomethod for Bayesian analysis of models with ill-behaved posteriordistributions. In order to sample efficiently from such a distribution,a location-scale transformation and a transformation to polarcoordinates are used. After...
Persistent link: https://www.econbiz.de/10011256462
Adaptive Polar Sampling (APS) is proposed as a Markov chain Monte Carlo method for Bayesian analysis of models with ill-behaved posterior distributions. In order to sample efficiently from such a distribution, a location-scale transformation and a transformation to polar coordinates are used....
Persistent link: https://www.econbiz.de/10005137171
sophisticated neural network simulation techniques is explored. In all examples considered in this paper – a bimodal distribution of …
Persistent link: https://www.econbiz.de/10011374406
Adaptive Polar Sampling (APS) is proposed as a Markov chain Monte Carlomethod for Bayesian analysis of models with ill-behaved posteriordistributions. In order to sample efficiently from such a distribution,a location-scale transformation and a transformation to polarcoordinates are used. After...
Persistent link: https://www.econbiz.de/10011302625
Accurate prediction of risk measures such as Value at Risk (VaR) and Expected Shortfall (ES) requires precise estimation of the tail of the predictive distribution. Two novel concepts are introduced that offer a specific focus on this part of the predictive density: the censored posterior, a...
Persistent link: https://www.econbiz.de/10011255481
Divergent priors are improper when defined on unbounded supports. Bartlett's paradox has been taken to imply that using improper priors results in ill-defined Bayes factors, preventing model comparison by posterior probabilities. However many improper priors have attractive properties that...
Persistent link: https://www.econbiz.de/10011255610
simulation methods are studied for the case of highly non-elliptical posterior distributions. A comparative analysis is presented … of possible advantages and limitations of different simulation techniques; of possible choices of candidate distributions …
Persistent link: https://www.econbiz.de/10011255693
sophisticated neural network simulation techniques is explored. In all examples considered in this paper – a bimodal distribution of …
Persistent link: https://www.econbiz.de/10011255771
This paper presents the R package MitISEM, which provides an automatic and flexible method to approximate a non-elliptical target density using adaptive mixtures of Student-t densities, where only a kernel of the target density is required. The approximation can be used as a candidate density in...
Persistent link: https://www.econbiz.de/10011255807
We summarize the general combination approach by Billio et al. [2010]. In the combination model the weights follow logistic autoregressive processes, change over time and their dynamics are possible driven by the past forecasting performances of the predictive densities. For illustrative...
Persistent link: https://www.econbiz.de/10011255843