Learning to Average Predictively over Good and Bad: Comment on: Using Stacking to Average Bayesian Predictive Distributions

By Lennart F. Hoogerheide, H. V. Dijk. 2018

82 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Andrew Gelman
2. Daniel P. Simpson
3. Aki Vehtari
4. Yuling Yao
5. J. Frieden
6. Harini Suresh
7. Chase Foster
8. John V. Guttag

In Finance

1. Andrew Gelman
2. Daniel P. Simpson
3. Aki Vehtari
4. Yuling Yao

In Management Science and Operations Research

1. Andrew Gelman
2. Daniel P. Simpson
3. Shira Mitchell
4. Solon Barocas
5. Aki Vehtari
6. Eric Potash
7. Yuling Yao

Citations in the corpus

• Prediction-Based Decisions and Fairness: A Catalogue of Choices, Assumptions, and Definitions (2018, background): “Combining all choices in one expanded model [129] can mitigate sensitivity of decisions to model selection.”
• Using Stacking to Average Bayesian Predictive Distributions (with Discussion) (2017, methodology): “For example (Yao et al., 2018, end of Section 3.1) cite the generic properties that log score is local and proper as a reason for adopting it.”