| Name : R-baycn
| |
| Version : 1.2.0
| Vendor : obs://build_opensuse_org/devel:languages:R
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| Release : lp153.14.4
| Date : 2024-06-14 11:57:44
|
| Group : Development/Libraries/Other
| Source RPM : R-baycn-1.2.0-lp153.14.4.src.rpm
|
| Size : 3.93 MB
| |
| Packager : (none)
| |
| Summary : Bayesian Inference for Causal Networks
|
Description :
A Bayesian hybrid approach for inferring Directed Acyclic Graphs (DAGs)
for continuous, discrete, and mixed data. The algorithm can use the
graph inferred by another more efficient graph inference method as
input; the input graph may contain false edges or undirected edges but
can help reduce the search space to a more manageable size. A Bayesian
Markov chain Monte Carlo algorithm is then used to infer the
probability of direction and absence for the edges in the network.
References: Martin and Fu (2019) < arXiv:1909.10678>.
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RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
