Fetching the paper…
Reading the bibliography…
We propose a new approach to Bayesian prediction that caters for models with a large number of parameters and is robust to model misspecification.
Merging of opinions with increasing information
David Blackwell and Lester Dubins · 1962
Earlier work this paper cites.
Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root?
Denis Kwiatkowski, Peter C.B. Phillips, Peter Schmidt, and Yongcheol Shin · 1992
Earlier work this paper cites.
Asymptotic theory for the GARCH(1, 1) quasi-maximum likelihood estimator
Sang-Won Lee and Bruce E Hansen · 1994
Earlier work this paper cites.
Specification, estimation, and evaluation of smooth transition autoregressive models
Timo Teräsvirta · 1994
Earlier work this paper cites.
Weak Convergence and Empirical Processes: With Applications to Statistics
AW van der Vaart and Jon Wellner · 1996
Earlier work this paper cites.
Rates of convergence of posterior distributions
Xiaotong Shen and Larry Wasserman · 2001
Earlier work this paper cites.
An MCMC approach to classical estimation
Victor Chernozhukov and Han Hong · 2003
Earlier work this paper cites.
Strictly proper scoring rules, prediction, and estimation
Tilmann Gneiting and Adrian E Raftery · 2007
Earlier work this paper cites.
Probabilistic forecasts, calibration and sharpness
Tilmann Gneiting, Fadoua Balabdaoui, and Adrian E Raftery · 2007
Earlier work this paper cites.
Gibbs posterior for variable selection in high-dimensional classification and data-mining
Wenxin Jiang and Martin A. Tanner · 2008
Earlier work this paper cites.
Likelihood-based scoring rules for comparing density forecasts in tails
Cees Diks, Valentyn Panchenko, and Dick Van Dijk · 2011
Earlier work this paper cites.
Time-varying combinations of predictive densities using nonlinear filtering
M Billio, R Casarin, F Ravazzolo, and H.K. van Dijk · 2013
Earlier work this paper cites.
Ergodicity of observation-driven time series models and consistency of the maximum likelihood estimator
Randal Douc, Paul Doukhan, and Eric Moulines · 2013
Earlier work this paper cites.
A Bayesian beta Markov random field calibration of the term structure of implied risk neutral densities
Roberto Casarin, Fabrizio Leisen, German Molina, and Enrique ter Horst · 2015
Earlier work this paper cites.
Probabilistic backpropagation for scalable learning of Bayesian neural networks
José Miguel Hernández-Lobato and Ryan Adams · 2015
Earlier work this paper cites.
On the properties of variational approximations of Gibbs posteriors
Pierre Alquier, James Ridgway, and Nicolas Chopin · 2016
Earlier work this paper cites.
A nonparametric model for stationary time series
Isadora Antoniano-Villalobos and Stephen G Walker · 2016
Earlier work this paper cites.
A general framework for updating belief distributions
Pier Giovanni Bissiri, Chris C Holmes, and Stephen G Walker · 2016
Earlier work this paper cites.
Optimal portfolio choice under decision-based model combinations
Davide Pettenuzzo and Francesco Ravazzolo · 2016
Cited alongside, same era.
Variational inference: A review for statisticians
David M Blei, Alp Kucukelbir, and Jon D McAuliffe · 2017
Cited alongside, same era.
Fundamentals of Nonparametric Bayesian Inference , volume 44
Subhashis Ghosal and Aad Van der Vaart · 2017
Cited alongside, same era.
Objective Bayesian inference with proper scoring rules
Federica Giummolè, Valentina Mameli, Erlis Ruli, and Laura Ventura · 2017
Cited alongside, same era.
Assigning a value to a power likelihood in a general Bayesian model
CC Holmes and SG Walker · 2017
Cited alongside, same era.
Variational Bayes with intractable likelihood
Minh-Ngoc Tran, David J Nott, and Robert Kohn · 2017
Cited alongside, same era.
Card forecasts for M4
Jurgen A Doornik, Jennifer L Castle, and David F Hendry · 2020
Later among the works it cites.
Groec: Combination method via generalized rolling origin evaluation
Jose Augusto Fiorucci and Francisco Louzada · 2020
Later among the works it cites.
Focused Bayesian prediction
Ruben Loaiza-Maya, Gael M Martin, and David T Frazier · 2020
Later among the works it cites.
The M4 competition: 100,000 time series and 61 forecasting methods
Spyros Makridakis, Evangelos Spiliotis, and Vassilios Assimakopoulos · 2020
Later among the works it cites.
Multivariate Bayesian predictive synthesis in macroeconomic forecasting
Kenichiro McAlinn, Knut Are Aastveit, Jouchi Nakajima, and Mike West · 2020
Later among the works it cites.
FFORMA: Feature-based forecast model averaging
Pablo Montero-Manso, George Athanasopoulos, Rob J Hyndman, and Thiyanga S Talagala · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Bayesian nonparametric calibration and combination of predictive distributions
Federico Bassetti, Roberto Casarin, and Francesco Ravazzolo · 2018
Cited alongside, same era.
Gaussian variational approximation for high-dimensional state space models
Matias Quiroz, David J Nott, and Robert Kohn · 2018
Cited alongside, same era.
Forecast density combinations of dynamic models and data driven portfolio strategies
N Baştürk, A. Borowska, S. Grassi, L. Hoogerheide, and H.K. van Dijk · 2019
Cited alongside, same era.
Approximate Bayesian forecasting
David T Frazier, Worapree Maneesoonthorn, Gael M Martin, and Brendan PM McCabe · 2019
Cited alongside, same era.
An introduction to variational autoencoders
Diederik P Kingma and Max Welling · 2019
Cited alongside, same era.
Generalized variational inference: Three arguments for deriving new posteriors
Jeremias Knoblauch, Jack Jewson, and Theodoros Damoulas · 2019
Cited alongside, same era.
A simple combination of univariate models
Fotios Petropoulos and Ivan Svetunkov · 2020
Later among the works it cites.
A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting
Slawek Smyl · 2020
Later among the works it cites.
Gibbs posterior concentration rates under sub-exponential type losses
Nicholas Syring and Ryan Martin · 2020
Later among the works it cites.
Alpha-variational inference with statistical guarantees
Yun Yang, Debdeep Pati, Anirban Bhattacharya, et al · 2020
Later among the works it cites.
Convergence rates of variational posterior distributions
Fengshuo Zhang and Chao Gao · 2020
Later among the works it cites.
User-friendly introduction to pac-bayes bounds
Pierre Alquier · 2021
Closest in time.
A note on the accuracy of variational Bayes in state space models: Inference and prediction
David T Frazier, Ruben Loaiza-Maya, and Gael M Martin · 2021
Closest in time.
Asymptotic normality, concentration, and coverage of generalized posteriors
Jeffrey W Miller · 2021
Closest in time.
Generalized Bayesian likelihood-free inference using scoring rules estimators
Lorenzo Pacchiardi and Ritabrata Dutta · 2021
Closest in time.
Calibrating generalized predictive distributions
Pei-Shien Wu and Ryan Martin · 2021
Closest in time.
Optimal probabilistic forecasts: When do they work?
Gael M Martin, Rubén Loaiza-Maya, Worapree Maneesoonthorn, David T Frazier, and Andrés Ramírez-Hassan · 2022
Closest in time.