A Structural Equation Embedded Likelihood Framework for Causal Discovery

Provides the SELF criteria to learn causal structure. Please cite "Ruichu Cai, Jie Qiao, Zhenjie Zhang, Zhifeng Hao. SELF: Structural Equational Embedded Likelihood Framework for Causal Discovery. AAAI. 2018."


Overview

Provides the SELF criteria to learn causal structure.

Details of the algorithm can be found in "SELF: A Structural Equation Embedded Likelihood Framework for Causal Discovery" (AAAI2018).

Installation

install.packages("SELF")

Quick Start

This package contain the data synthetic process and the casual structure learning algorithm. Here are some examples to make a quick start:

#x->y->z
set.seed(0)
x=rnorm(4000)
y=x^2+runif(4000,-1,1)*0.1
z=y^2+runif(4000,-1,1)*0.1
data=data.frame(x,y,z)
fhc(data,gamma=10,booster = "gbtree")
 
#x->y->z linear data
set.seed(0)
x=rnorm(4000)
y=3*x+runif(4000,-1,1)*0.1
z=3*y+runif(4000,-1,1)*0.1
data=data.frame(x,y,z)
fhc(data,booster = "lm")
 
#RandomGraph linear data
set.seed(0)
G=randomGraph(dim=10,indegree=1.5)
data=synthetic_data_linear(G=G,sample_num=4000)
fitG=fhc(data,booster = "lm")
indicators(fitG,G)

News

SELF 0.1.1

  • Added new parameter maxite to randomGraph
  • Improve the help documentation.

SELF 0.1.0

  • Added a NEWS.md file to track changes to the package.

Reference manual

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install.packages("SELF")

0.1.1 by Jie Qiao, a year ago


Browse source code at https://github.com/cran/SELF


Authors: Ruichu Cai [ths, aut] , Jie Qiao [aut, cre] , Zhenjie Zhang [ths, aut] , Zhifeng Hao [ths, aut]


Documentation:   PDF Manual  


GPL-2 license


Imports data.table, xgboost, Rcpp, CompareCausalNetworks, bnlearn

Linking to Rcpp


See at CRAN