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Variational Bayes for assessment of dynamic quantile forecasts

Gerlach, Richard; Abeywardana, Sachin - In: International journal of forecasting 32 (2016) 4, pp. 1385-1402

Persistent link: https://www.econbiz.de/10011622172

Bayesian assessment of dynamic quantile forecasts

Gerlach, Richard; Chen, Cathy W. S.; Lin, Edward M. H. - In: Journal of forecasting 35 (2016) 8, pp. 751-764

Persistent link: https://www.econbiz.de/10011633826

A Class of Adaptive Importance Sampling Weighted EM Algorithms for Efficient and Robust Posterior and Predictive Simulation

Hoogerheide, Lennart F. - 2012

A class of adaptive sampling methods is introduced for efficient posterior and predictive simulation. The proposed … between target and mixture is minimized. We label this approach <I>Mixture of t by Importance Sampling and Expectation … Importance Sampling (IS) or the Metropolis-Hastings (MH) method. We also introduce three extensions of the basic MitISEM approach …

Persistent link: https://www.econbiz.de/10013108670

Bayesian forecasting of federal funds target rate decisions

Hauwe, Sjoerd van den; Paap, Richard; Dijk, Dick van - In: Journal of macroeconomics 37 (2013), pp. 19-40

Persistent link: https://www.econbiz.de/10010237941

Bayesian calibration of generalized pools of predictive distributions

Casarin, Roberto; Mantoan, Giulia; Ravazzolo, Francesco - In: Econometrics : open access journal 4 (2016) 1, pp. 1-24

Decision-makers often consult different experts to build reliable forecasts on variables of interest. Combining more opinions and calibrating them to maximize the forecast accuracy is consequently a crucial issue in several economic problems. This paper applies a Bayesian beta mixture model to...

Persistent link: https://www.econbiz.de/10011505901

Recovering the most entropic copulas from preliminary knowledge of dependence

Chu, Ba; Satchell, Stephen - In: Econometrics : open access journal 4 (2016) 2, pp. 1-21

This paper provides a new approach to recover relative entropy measures of contemporaneous dependence from limited information by constructing the most entropic copula (MEC) and its canonical form, namely the most entropic canonical copula (MECC). The MECC can effectively be obtained by...

Persistent link: https://www.econbiz.de/10011505976