brms: R2D2 – R documentation

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R2D2

R2-D2 Priors in brms

Description

Function used to set up R2D2 priors for population-level effects in brms. The function does not evaluate its arguments – it exists purely to help set up the model.

Usage

R2D2(mean_R2 = 0.5, prec_R2 = 2, cons_D2 = 1, autoscale = TRUE)

Arguments

`mean_R2`	mean of the Beta prior on the coefficient of determination R^2.
`prec_R2`	precision of the Beta prior on the coefficient of determination R^2.
`cons_D2`	concentration vector of the Dirichlet prior on the variance decomposition parameters.
`autoscale`	Logical; indicating whether the horseshoe prior should be scaled using the residual standard deviation `sigma` if possible and sensible (defaults to `TRUE`). Autoscaling is not applied for distributional parameters or when the model does not contain the parameter `sigma`.

References

Zhang, Y. D., Naughton, B. P., Bondell, H. D., & Reich, B. J. (2020). Bayesian regression using a prior on the model fit: The R2-D2 shrinkage prior. Journal of the American Statistical Association. https://arxiv.org/pdf/1609.00046.pdf

Examples

set_prior(R2D2(mean_R2 = 0.8, prec_R2 = 10))

brms

Bayesian Regression Models using 'Stan'

v2.15.0

GPL-2

Authors

Paul-Christian Bürkner [aut, cre], Jonah Gabry [ctb], Sebastian Weber [ctb], Andrew Johnson [ctb], Martin Modrak [ctb]

Initial release

2021-03-10