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cbl  

Causal Discovery under a Confounder Blanket
View on CRAN: Click here


Download and install cbl package within the R console
Install from CRAN:
install.packages("cbl")

Install from Github:
library("remotes")
install_github("cran/cbl")

Install by package version:
library("remotes")
install_version("cbl", "0.1.3")



Attach the package and use:
library("cbl")
Maintained by
David Watson
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-06-10
Latest Update: 2022-12-20
Description:
Methods for learning causal relationships among a set of foreground variables X based on signals from a (potentially much larger) set of background variables Z, which are known non-descendants of X. The confounder blanket learner (CBL) uses sparse regression techniques to simultaneously perform many conditional independence tests, with complementary pairs stability selection to guarantee finite sample error control. CBL is sound and complete with respect to a so-called "lazy oracle", and works with both linear and nonlinear systems. For details, see Watson & Silva (2022) .
How to cite:
David Watson (2022). cbl: Causal Discovery under a Confounder Blanket. R package version 0.1.3, https://cran.r-project.org/web/packages/cbl. Accessed 03 Dec. 2024.
Previous versions and publish date:
0.1.1 (2022-06-17 11:40), 0.1.2 (2022-11-16 23:40), 0.1 (2022-06-10 11:10)
Other packages that cited cbl R package
View cbl citation profile
Other R packages that cbl depends, imports, suggests or enhances
Complete documentation for cbl
Functions, R codes and Examples using the cbl R package
Some associated functions: bipartite . cbl . epsilon_fn . l0 . minD . r.TailProbs . ss_fn . sub_loop . 
Some associated R codes: bipartite.R . cbl.R . shah_ss.R . utils.R .  Full cbl package functions and examples
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