A Structural Equation Embedded Likelihood Framework for Causal
Discovery
c(
person("Ruichu","Cai",email="cairuichu@gmail.com",role=c("ths")),
person("Jie","Qiao",email="qiaojie2004@vip.qq.com",role=c("aut","cre")),
person("Zhenjie","Zhang",email="zhenjie@adsc.com.sg",role=c("ths")),
person("Zhifeng","Hao",email="zfhao@gdut.edu.cn",role=c("ths"))
)
Ruichu Cai [ths],
Jie Qiao [aut, cre],
Zhenjie Zhang [ths],
Zhifeng Hao [ths]
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" (AAAI 2018).

c(
person("Ruichu","Cai",email="cairuichu@gmail.com",role=c("ths","aut")),
person("Jie","Qiao",email="qiaojie2004@vip.qq.com",role=c("aut","cre")),
person("Zhenjie","Zhang",email="zhenjie@adsc.com.sg",role=c("ths","aut")),
person("Zhifeng","Hao",email="zfhao@gdut.edu.cn",role=c("ths","aut"))
)
Ruichu Cai [ths, aut],
Jie Qiao [aut, cre],
Zhenjie Zhang [ths, aut],
Zhifeng Hao [ths, aut]
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."

Identifiability of linear structural equation models
Rina Foygel <rina@uchicago.edu>, Mathias Drton <md5@uw.edu>.
This package provides routines to check identifiability or
non-identifiability of linear structural equation models as
described in Drton, Foygel & Sullivant (Ann. Statist., 2011)
and Foygel, Draisma & Drton (Ann. Statist., 2012).  The
routines are based on the graphical representation of
structural equation models by a path diagram/mixed graph.

This package provides routines to check identifiability or non-identifiability of linear structural equation models as described in Drton, Foygel & Sullivant (Ann. Statist., 2011) and Foygel, Draisma & Drton (Ann. Statist., 2012).  The routines are based on the graphical representation of structural equation models by a path diagram/mixed graph.