We demonstrate that the forecasting combination puzzle is a consequence ...
This paper explores the implications of producing forecast distributions...
The Bayesian statistical paradigm provides a principled and coherent app...
This paper takes the reader on a journey through the history of Bayesian...
We investigate the performance and sampling variability of estimated for...
Approximate Bayesian computation (ABC) has advanced in two decades from ...
The 21st century has seen an enormous growth in the development and use ...
Using theoretical and numerical results, we document the accuracy of com...
We propose a new method for Bayesian prediction that caters for models w...
Proper scoring rules are used to assess the out-of-sample accuracy of
pr...
The Bayesian statistical paradigm uses the language of probability to ex...
We propose a new method for conducting Bayesian prediction that delivers...
We investigate the impact of filter choice on forecast accuracy in state...
We use the jackknife to bias correct the log-periodogram regression (LPR...
Approximate Bayesian Computation (ABC) has become increasingly prominent...
The focus of this paper is on the quantification of sampling variation i...