| Name : R-UPG
| |
| Version : 0.3.4
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.2.2
| Date : 2024-06-14 11:51:46
|
| Group : Development/Libraries/Other
| Source RPM : R-UPG-0.3.4-lp153.2.2.src.rpm
|
| Size : 0.61 MB
| |
| Packager : (none)
| |
| Summary : Efficient Bayesian Algorithms for Binary and Categorical Data Regression Models
|
Description :
Efficient Bayesian implementations of probit, logit, multinomial logit
and binomial logit models. Functions for plotting and tabulating the
estimation output are available as well. Estimation is based on Gibbs
sampling where the Markov chain Monte Carlo algorithms are based on the
latent variable representations and marginal data augmentation
algorithms described in \"Gregor Zens, Sylvia Frühwirth-Schnatter &
Helga Wagner (2023). Ultimate Pólya Gamma Samplers – Efficient MCMC for
possibly imbalanced binary and categorical data, Journal of the
American Statistical Association < doi:10.1080/01621459.2023.2259030>\".
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
