1 citations · 1 across the 5 of their papers we have counts for
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Pseudo-R2D2 prior for high-dimensional ordinal regression
Eric Yanchenko
Ordinal regression with a high-dimensional covariate space has many important application areas including gene expression studies. The lack of an intrinsic numeric value associated…
The Group R2D2 Shrinkage Prior for Sparse Linear Models with Grouped Covariates
Eric Yanchenko, Kaoru Irie, Shonosuke Sugasawa
Shrinkage priors are a popular Bayesian paradigm to handle sparsity in high-dimensional regression. Still limited, however, is a flexible class of shrinkage priors to handle groupe…
Mediation analysis of community context effects on heart failure using the survival R2D2 prior
Brandon R. Feng, Eric Yanchenko, K. Lloyd Hill +3
Congestive heart failure (CHF) is a leading cause of morbidity, mortality and healthcare costs, impacting 23 million individuals worldwide. Large electronic health records data…
Spatial regression modeling via the R2D2 framework
Eric Yanchenko, Howard D. Bondell, Brian J. Reich
Spatially dependent data arises in many applications, and Gaussian processes are a popular modelling choice for these scenarios. While Bayesian analyses of these problems have prov…
The R2D2 Prior for Generalized Linear Mixed Models
Eric Yanchenko, Howard D. Bondell, Brian J. Reich
In Bayesian analysis, the selection of a prior distribution is typically done by considering each parameter in the model. While this can be convenient, in many scenarios it may be…