Concept

Definition of Pairwise Causal and Non-causal Relationship (in the book)

The authors consider that pairs of variables X and Y can be in one of four types of relationships:

  • X causes Y ( X → Y )
  • Y causes X ( X ← Y )
  • X and Y are dependent, but not in a causal relationship ( X :left_right_arrow: Y )
  • X and Y are independent ( X ⊥ Y ). Any pair of variables ( X , Y ) is associated with one and only one such relationships, called “ground truth” G . By definition, we have: G=[XY]fNys.t.Y:=f(X,Ny)G=[X\rightarrow Y] \Rightarrow \exists f \wedge \exists N_y s.t. Y:=f(X,N_y) G=[XY]fNxs.t.X:=f(Y,Nx)G=[X\leftarrow Y] \Rightarrow \exists f \wedge \exists N_x s.t. X:=f(Y,N_x) G=[XY]f,gNx,Ny,Zs.t.X:=f(Z,Nx)y:=f(Z,Ny)G=[X\leftrightarrow Y] \Rightarrow \exists f,g \wedge \exists N_x, N_y, Z s.t. X:= f(Z,N_x)\wedge y:= f(Z,N_y) G=XYG= X ⊥ Y X and Y are independent, no functional relationship

The authors do not necessarily assume that ( X ⊥ N y ) nor that ( Y ⊥ N x ), thus there can be additional latent confounders in the first two cases X → Y and X ← Y.

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Updated 2020-07-17

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Data Science