Conjugate priors for generalized linear models

84 citations recorded by the source corpus.

How researchers see this paper

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

Model Averaging and Its Use in Economics (2017, methodology): “This idea was already used in the conjugate prior proposed by Chen and Ibrahim (2003),”
Mixtures of g-Priors in Generalized Linear Models (2015, methodology): “…derivation of the g-prior, priors based on imaginary data have been developed in the context of GLMs by Bedrick, Christensen, and Johnson (1996); Chen and Ibrahim (2003); Sabanés Bové and Held (2011); Perrakis, Fouskakis, andNtzoufras (2015); Fouskakis, Ntzoufras, and Perrakis (2018) among…”
The Power Prior: Theory and Applications (2015, background): “Many other interesting special cases for the specification of y0 as well as the elicitation of a0 for GLMs can be found in [53].”
Coupled Kernel Embedding for Low-Resolution Face Image Recognition (2012, background): “Compared with highresolution (HR) images, these LR images lose some discriminative details across different subjects.”
Bayesian Hierarchical Models With Conjugate Full-Conditional Distributions for Dependent Data From the Natural Exponential Family (2017, methodology): “Similar to the special cases that emerged from Diaconis and Ylvisaker (1979) we obtain Poisson/multivariate log-gamma (MLG), binomial/multivariate logit beta, negative binomial/multivariate logit beta, and gamma/multivariate negative-inverse-gamma hierarchical models (Chen and Ibrahim, 2003).”