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BCDAG
View on CRAN: Click
here
Download and install BCDAG package within the R console
Install from CRAN:
install.packages("BCDAG")
Install from Github:
library("remotes")
install_github("cran/BCDAG")
Install by package version:
library("remotes")
install_version("BCDAG", "1.1.1")
Attach the package and use:
library("BCDAG")
Maintained by
Alessandro Mascaro
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-03-15
Latest Update: 2024-02-10
Description:
A collection of functions for structure learning of causal networks and estimation of joint causal effects from observational Gaussian data. Main algorithm consists of a Markov chain Monte Carlo scheme for posterior inference of causal structures, parameters and causal effects between variables.
References:
F. Castelletti and A. Mascaro (2021) ,
F. Castelletti and A. Mascaro (2022) .
How to cite:
Alessandro Mascaro (2022). BCDAG: Bayesian Structure and Causal Learning of Gaussian Directed Graphs. R package version 1.1.1, https://cran.r-project.org/web/packages/BCDAG. Accessed 22 Dec. 2024.
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Complete documentation for BCDAG
Functions, R codes and Examples using
the BCDAG R package
Some associated functions: DW_nodelml . acceptreject_DAG . bd_decode . bd_encode . causaleffect . fa . get_MAPdag . get_MPMdag . get_causaleffect . get_diagnostics . get_edgeprobs . get_opcard . learn_DAG . leukemia . new_bcdag . operation . pa . propose_DAG . rDAG . rDAGWishart . rnodeDAGWishart . summary.bcdag .
Some associated R codes: DW_nodelml.R . acceptreject_DAG.R . bd_decode.R . bd_encode.R . causaleffect.R . fa.R . get_MAPdag.R . get_MPMdag.R . get_causaleffect.R . get_diagnostics.R . get_edgeprobs.R . get_opcard.R . globals.R . learn_DAG.R . leukemia.R . new_bcdag.R . operation.R . pa.R . propose_DAG.R . rDAG.R . rDAGWishart.R . rnodeDAGWishart.R . summary.bcdag.R . validate_bcdag.R . Full BCDAG package functions and examples
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