DAG_from_Ordering: Infer DAG using topological ordering

In WY-Chen/EqVarDAG: Causal Discovery with Equal Variance Assumption

Infer DAG using topological ordering

Description

Infer DAG using topological ordering

Usage

DAG_from_Ordering(
  X,
  TO,
  mtd = "ztest",
  alpha = 0.05,
  threshold = 0.1,
  FCD = NULL,
  precmtd = NULL
)

Arguments

X:	data in n x p matrix
TO:	topological ordering
alpha:	desired selection significance level
mtd:	methods for learning DAG from topological orderings. "ztest": (p<n) [Multiple Testing and Error Control in Gaussian Graphical Model Selection. Drton and Perlman.2007] "rls": (p<n) fit recursive least squares using ggm package and threshold the regression coefs "chol": (p<n) perform cholesky decomposition and threshold the regression coefs "dlasso": debiased lasso (default with FCD=True and precmtd="sqrtlasso"); "lasso": lasso with fixed lambda from [Penalized likelihood methods for estimation of sparse high-dimensional directed acyclic graphs. Shojaie and Michailidis. 2010]; "adalasso": adaptive lasso with fixed lambda from [Shojaie and Michailidis. 2010]; "cvlasso": cross-validated lasso from glmnet; "scallasso": scaled lasso.
threshold:	only used in rls and chol. the hard threshold level.
FCD:	only used in debiased lasso, the FCD procedure [False Discovery Rate Control via Debiased Lasso. Javanmard and Montanari. 2018] or use individual tests to select support.
precmtd:	only used in debiased lasso, how to compute debiasing matrix "cv": node-wise lasso w/ joint 10 fold cv "sqrtlasso": square-root lasso (no tune, default)

Value

Adjacency matrix with ADJ[i,j]!=0 iff i->j

WY-Chen/EqVarDAG documentation built on May 10, 2022, 7:08 a.m.