path_to_network {SEset}

Precision matrix from ordered path model

Description

Takes a path model and generates the corresponding (standardized) precision matrix or covariance matrix. The inverse of network_to_path.

Usage

path_to_network(B, psi = NULL, output = "precision")

Arguments

B

input p \times p weights matrix

psi

variance-covariance matrix for the residuals. If NULL (the default) will impose the constraint that the variables have variance 1 and the residuals are uncorrelated

output

Function returns the precision ("precision") or covariance ("covariance") matrix

Value

a p \times p precision or covariance matrix

References

Ryan O, Bringmann LF, Schuurman NK (upcoming). “The challenge of generating causal hypotheses using network models.” in preperation.

Shojaie A, Michailidis G (2010). “Penalized likelihood methods for estimation of sparse high-dimensional directed acyclic graphs.” Biometrika, 97(3), 519–538.

Bollen KA (1989). Structural equations with latent variables. Oxford, England, John Wiley \& Sons.

See Also

network_to_path, SEset_to_network