grangersearch

An R package for exhaustive Granger causality testing with tidyverse integration.

Overview

grangersearch provides a simple interface for performing Granger causality tests on time series data. The package wraps the vars infrastructure while providing a streamlined interface for exploratory causal analysis.

Key features include:

• Exhaustive pairwise search: Automatically discover Granger-causal relationships across multiple variables
• Automatic lag optimization: Systematic evaluation of multiple lag orders with visualization
• Tidyverse compatibility: Pipe operators (|>, %>%) and non-standard evaluation
• Broom integration: tidy() and glance() methods for structured output
• Visualization: Built-in plotting for causality matrices and lag selection analysis

Installation

Install from GitHub:

# install.packages("remotes")
remotes::install_github("nkorf/grangersearch")

Quick Start

library(grangersearch)

# Basic pairwise test
data(Canada, package = "vars")
result <- Canada |> granger_causality_test(e, U, lag = 2)
print(result)

# Get tidy results
tidy(result)

# Exhaustive search across multiple variables
search_results <- Canada |> granger_search(lag = 2)
plot(search_results)  # Causality matrix visualization

# Lag selection analysis
lag_analysis <- Canada |> granger_lag_select(e, U, lag = 1:8)
plot(lag_analysis)

Main Functions

Example Output

Granger Causality Test
======================

Observations: 84, Lag order: 2, Significance level: 0.050

e -> U: e Granger-causes U (p = 0.0000)
U -> e: U does not Granger-cause e (p = 0.2983)

Citation

If you use this package, please cite:

Korfiatis, N. (2025). grangersearch: An R Package for Exhaustive Granger Causality Testing with Tidyverse Integration. arXiv preprint. https://arxiv.org/abs/XXXX.XXXXX

Author

Nikolaos Korfiatis Department of Informatics, Ionian University Corfu, Greece nkorf@ionio.gr

License

MIT