| Name : R-SeBR
| |
| Version : 1.0.0
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.2.5
| Date : 2024-06-14 11:57:48
|
| Group : Development/Libraries/Other
| Source RPM : R-SeBR-1.0.0-lp153.2.5.src.rpm
|
| Size : 0.71 MB
| |
| Packager : (none)
| |
| Summary : Semiparametric Bayesian Regression Analysis
|
Description :
Monte Carlo and MCMC sampling algorithms for semiparametric Bayesian
regression analysis. These models feature a nonparametric (unknown)
transformation of the data paired with widely-used regression models
including linear regression, spline regression, quantile regression,
and Gaussian processes. The transformation enables broader
applicability of these key models, including for real-valued, positive,
and compactly-supported data with challenging distributional features.
The samplers prioritize computational scalability and, for most cases,
Monte Carlo (not MCMC) sampling for greater efficiency. Details of the
methods and algorithms are provided in Kowal and Wu (2023)
< arXiv:2306.05498>.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
