Rel 0.1.0

Author: goedman

docs/src/index.md

@@ -1,6 +1,15 @@
 ```@meta
 CurrentModule = StructuralCausalModels
 ```
+## StructuralCausalModels
+```@docs
+StructuralCausalModels
+```
+
+## SCM
+```@docs
+SCM
+```
 
 ## scm_path
 ```@docs
@@ -72,6 +81,7 @@ node_edges(p::Path, s::Symbol, l::Symbol)
 open_paths(d::DAG, paths::Vector{Vector{Symbol}}, cond::Vector{Symbol};debug=false)
 pcor(d::DAG, u::SymbolList)
 pcor_test(d::DAG, u::SymbolList, q, n)
+ribbon_graph(a::NamedArray{Int, 2}; m=Symbol[], c=Symbol[])
 sym_in_all_paths(paths, sym)
 syms_in_paths(paths, f, l)
 topological_order(a::NamedArray)

src/StructuralCausalModels.jl

@@ -1,6 +1,6 @@
 """
 
-# StructuralCausalModels (SCM)
+# StructuralCausalModels
 
 StructuralCausalModels.jl provides functionality to analyse directed acyclic
 graph (DAG) based causal models as described in `StatisticalRethinking`, `Causal
@@ -9,6 +9,8 @@ Inference in Statistics` and `Cause and Correlation in Biology`.
 My initial goal for this package is to have a way to apply SCM ideas to the
 examples in the context of StatisticalRethinking, i.e. a working version of
 `basis_set()`, `d_separation()`, `m_separation()` and `adjustment_sets()`.
+
+SCM can be used as an alias to StructuralCausalModels.
 """
 module StructuralCausalModels
 
@@ -23,6 +25,13 @@ src_path = @__DIR__
 using DocStringExtensions: SIGNATURES, FIELDS, TYPEDEF
 
 const scm_src_path = @__DIR__
+
+"""
+
+SCM
+
+Alias for StructuralCausalModels
+"""
 const SCM = StructuralCausalModels
 
 """

test/test_m_separation.jl

@@ -20,7 +20,7 @@ f = [:n1]
 s = [:n4]
 c = [:n3]
 
-ms1 = m_separation(dag, f, s; debug=false)
+ms1 = m_separation(dag, f, s; debug=true)
 ms2 = m_separation(dag, f, s; c=c)
 
 @testset "m_separation" begin