Construct · 1 fields · 1 citations

stacking of predictive distributions: a standalone construct

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Bayesian statistics

a model-combination method that chooses weights for several models' predictive distributions to maximize leave-one-out predictive performance, as an alternative to Bayesian model averaging.

In Bayesian statistics, stacking of predictive distributions refers to a model-combination method that chooses weights for several models' predictive distributions to maximize leave-one-out predictive performance, as an alternative to Bayesian model averaging. This meaning comes from Yao (2018) in Bayesian Analysis.[1]

Unit
Recovery means
Measured by

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Nearby constructs

Bayesian model averaging1 fields · 1 citationsanchor · a standalone construct model3 fields · 3 citationsjingle · one word, three constructs performance6 fields · 8 citationsjingle · one word, five performances

References

Yao, Y., Vehtari, A., Simpson, D., & Gelman, A. (2018). Using Stacking to Average Bayesian Predictive Distributions (with Discussion). Bayesian Analysis, 13(3), 917-1007. https://doi.org/10.1214/17-ba1091

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