Description Usage Arguments Details Value Author(s) See Also Examples

This function computes partial correlations given a correlation matrix using a recursive algorithm.

1 |

`i,j` |
(integer) position of variable |

`k` |
(integer) positions of zero or more conditioning variables in the correlation matrix. |

`C` |
Correlation matrix (matrix) |

`cut.at` |
Number slightly smaller than one; if |

The partial correlations are computed using a recusive formula
if the size of the conditioning set is one. For larger conditioning
sets, the pseudoinverse of parts of the correlation matrix is
computed (by `pseudoinverse()`

from package
corpcor). The pseudoinverse instead of the inverse is used in
order to avoid numerical problems.

The partial correlation of i and j given the set k.

Markus Kalisch [email protected] and Martin Maechler

`condIndFisherZ`

for testing zero partial correlation.

1 2 3 4 5 6 7 8 9 10 11 | ```
## produce uncorrelated normal random variables
mat <- matrix(rnorm(3*20),20,3)
## compute partial correlation of var1 and var2 given var3
pcorOrder(1,2, 3, cor(mat))
## define graphical model, simulate data and compute
## partial correlation with bigger conditional set
genDAG <- randomDAG(20, prob = 0.2)
dat <- rmvDAG(1000, genDAG)
C <- cor(dat)
pcorOrder(2,5, k = c(3,7,8,14,19), C)
``` |

```
[1] 0.1919379
[1] 0.537579
```

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