impliedCovarianceMatrix: Implied Covariance Matrix of a Gaussian Graphical Model

In dagitty: Graphical Analysis of Structural Causal Models

Description

Implied Covariance Matrix of a Gaussian Graphical Model

Usage

impliedCovarianceMatrix(
  x,
  b.default = NULL,
  b.lower = -0.6,
  b.upper = 0.6,
  eps = 1,
  standardized = TRUE
)

Arguments

x	the input graph, a DAG (which may contain bidirected edges).
b.default	default path coefficient applied to arrows for which no coefficient is defined in the model syntax.
b.lower	lower bound for random path coefficients, applied if b.default=NULL.
b.upper	upper bound for path coefficients.
eps	residual variance (only meaningful if standardized=FALSE).
standardized	logical. If true, a standardized population covariance matrix is generated (all variables have variance 1).

dagitty documentation built on Jan. 21, 2021, 5:07 p.m.