HDGC_VAR_I0: Test Granger causality in High Dimensional Stationary VARs

In Marga8/HDGCvar: Granger Causality Testing in High Dimensional Vector Autoregressive Models

Test Granger causality in High Dimensional Stationary VARs

Description

Test Granger causality in High Dimensional Stationary VARs

Usage

HDGC_VAR_I0(
  GCpair,
  data,
  p = 1,
  bound = 0.5 * nrow(data),
  parallel = FALSE,
  n_cores = NULL
)

Arguments

GCpair	a named list with names GCto and GCfrom containing vectors of the relevant GC variables.
data	data matrix or object that can be coerced to a matrix.
p	lag length of the VAR
bound	lower bound on tuning parameter lambda
parallel	TRUE for parallel computing
n_cores	nr of cores to use in parallel computing, default is all but one

Value

LM Chi-square test statistics (asymptotic), LM F-stat with finite sample correction, both with their corresponding p-value. Lasso selections are also printed to the console.

References

Hecq, A., Margaritella, L., Smeekes, S., "Granger Causality Testing in High-Dimensional VARs: a Post-Double-Selection Procedure." arXiv preprint arXiv:1902.10991 (2019).

Examples

HDGC_VAR_I0(GCpair=list("GCto"="Var 1", "GCfrom"="Var 2"), data=sample_dataset_I0, p=2)

Marga8/HDGCvar documentation built on May 25, 2024, 11:12 a.m.