Supplementary Material for ‘Causal Discovery of Linear Cyclic Models from Multiple Experimental Data Sets with Overlapping Variables’
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چکیده
Hence B1,MvM = 1 and BM,1 = (I−BM,M)vM. Consider two possible cases. First, if (I − BM,M) is invertible we can ‘marginalize’ the variables in M, as The sum ∑∞ k=0(t(xi xj ||Jj)t(xj xi||Ji)) k is evaluated to 1/(1 − t(xi xj ||Jj)t(xj xi||Ji)) also when |t(xi xj ||Jj)t(xj xi||Ji)| > 1 (Hardy, 1949). discussed in (Hyttinen et al., 2012), to arrive at a linear cyclic model with a 1× 1 direct effects matrix B̃. The formula for marginalizing is
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تاریخ انتشار 2012