diff toolboxes/FullBNT-1.0.7/KPMstats/partial_corr_coef.m @ 0:e9a9cd732c1e tip

first hg version after svn

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/toolboxes/FullBNT-1.0.7/KPMstats/partial_corr_coef.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,28 @@
+function [r, c] = partial_corr_coef(S, i, j, Y)
+% PARTIAL_CORR_COEF Compute a partial correlation coefficient
+% [r, c] = partial_corr_coef(S, i, j, Y)
+%
+% S is the covariance (or correlation) matrix for X, Y, Z
+% where X=[i j], Y is conditioned on, and Z is marginalized out.
+% Let S2 = Cov[X | Y] be the partial covariance matrix.
+% Then c = S2(i,j) and r = c / sqrt( S2(i,i) * S2(j,j) ) 
+%
+
+% Example: Anderson (1984) p129
+% S = [1.0 0.8 -0.4;
+%     0.8 1.0 -0.56;
+%     -0.4 -0.56 1.0];
+% r(1,3 | 2) = 0.0966 
+%
+% Example: Van de Geer (1971) p111
+%S = [1     0.453 0.322;
+%     0.453 1.0   0.596;
+%     0.322 0.596 1];
+% r(2,3 | 1) = 0.533
+
+X = [i j];
+i2 = 1; % find_equiv_posns(i, X);
+j2 = 2; % find_equiv_posns(j, X);
+S2 = S(X,X) - S(X,Y)*inv(S(Y,Y))*S(Y,X);
+c = S2(i2,j2);
+r = c / sqrt(S2(i2,i2) * S2(j2,j2));