We demonstrate that the forecasting combination puzzle is a consequence ...
Bayesian inference is a powerful tool for combining information in compl...
Bayesian statistics is concerned with conducting posterior inference for...
We provide a general solution to a fundamental open problem in Bayesian
...
Simulation-based inference (SBI) techniques are now an essential tool fo...
Bayesian inference has widely acknowledged advantages in many problems, ...
The Bayesian statistical paradigm provides a principled and coherent app...
Likelihood-free inference (LFI) methods, such as Approximate Bayesian
co...
We present a procedure to diagnose model misspecification in situations ...
This paper takes the reader on a journey through the history of Bayesian...
Likelihood-free methods are an essential tool for performing inference f...
We investigate the performance and sampling variability of estimated for...
There has been much recent interest in modifying Bayesian inference for
...
Even in relatively simple settings, model misspecification can make the
...
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...
We analyse the behaviour of the synthetic likelihood (SL) method when th...
Likelihood-free methods are useful for parameter estimation of complex m...
Proper scoring rules are used to assess the out-of-sample accuracy of
pr...
We propose a novel approach to approximate Bayesian computation (ABC) th...
In many instances, the application of approximate Bayesian methods is
ha...
Indirect Inference (I-I) is a popular technique for estimating complex
p...
The Bayesian statistical paradigm uses the language of probability to ex...
We propose a new method for conducting Bayesian prediction that delivers...
Bayesian synthetic likelihood (BSL) is now a well-established method for...
Approximate Bayesian Computation (ABC) has become increasingly prominent...
Indirect inference requires simulating realizations of endogenous variab...