
Optimal probabilistic forecasts: When do they work?
Proper scoring rules are used to assess the outofsample accuracy of pr...
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Robust Approximate Bayesian Computation: An Adjustment Approach
We propose a novel approach to approximate Bayesian computation (ABC) th...
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Robust and Efficient Approximate Bayesian Computation: A Minimum Distance Approach
In many instances, the application of approximate Bayesian methods is ha...
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Approximate Maximum Likelihood for Complex Structural Models
Indirect Inference (II) is a popular technique for estimating complex p...
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Computing Bayes: Bayesian Computation from 1763 to the 21st Century
The Bayesian statistical paradigm uses the language of probability to ex...
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Focused Bayesian Prediction
We propose a new method for conducting Bayesian prediction that delivers...
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Robust Approximate Bayesian Inference with Synthetic Likelihood
Bayesian synthetic likelihood (BSL) is now a wellestablished method for...
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Approximate Bayesian Forecasting
Approximate Bayesian Computation (ABC) has become increasingly prominent...
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DerivativeBased Optimization with a NonSmooth Simulated Criterion
Indirect inference requires simulating realizations of endogenous variab...
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David T. Frazier
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