| Name : R-effectFusion
| |
| Version : 1.1.3
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.2.11
| Date : 2024-06-14 11:53:19
|
| Group : Development/Libraries/Other
| Source RPM : R-effectFusion-1.1.3-lp153.2.11.src.rpm
|
| Size : 0.31 MB
| |
| Packager : (none)
| |
| Summary : Bayesian Effect Fusion for Categorical Predictors
|
Description :
Variable selection and Bayesian effect fusion for categorical
predictors in linear and logistic regression models. Effect fusion aims
at the question which categories have a similar effect on the response
and therefore can be fused to obtain a sparser representation of the
model. Effect fusion and variable selection can be obtained either with
a prior that has an interpretation as spike and slab prior on the level
effect differences or with a sparse finite mixture prior on the level
effects. The regression coefficients are estimated with a flat
uninformative prior after model selection or by taking model averages.
Posterior inference is accomplished by an MCMC sampling scheme which
makes use of a data augmentation strategy (Polson, Scott & Windle
(2013) < doi:10.1080/01621459.2013.829001>) based on latent Polya-Gamma
random variables in the case of logistic regression. The code for data
augmentation is taken from Polson et al. (2013)
< doi:10.1080/01621459.2013.829001>, who own the copyright.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
