SEset_to_network {SEset} | R Documentation |
Precision matrices from the SEset
Description
Takes the SE-set and calculates for each weights matrix the corresponding
precision matrix. Used to check the results of network_to_SEset
to assess deviations from statistical equivalence induced due to rounding,
thresholding, and numerical approximations.
Usage
SEset_to_network(
SEmatrix,
order.ref = NULL,
order.mat = NULL,
output = "raw",
omega = NULL
)
Arguments
SEmatrix |
a |
order.ref |
an optional character vector with variable names, the reference ordering of the precision matrix. |
order.mat |
a |
output |
Output as |
omega |
Comparision precision matrix, e.g. original input precision matrix to
|
Value
If output = "raw"
, a n \times p
matrix of precision matrices
stacked column-wise in n
rows.
If output = "summary"
returns a list containing the bias, MSE and
RMSE for each re-calculated precision matrix, relative to comparison omega
matrix supplied.
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
, path_to_network