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Research PaperResearchia:202601.0490c703

grangersearch: An R Package for Exhaustive Granger Causality Testing with Tidyverse Integration

Nikolaos Korfiatis

Abstract

This paper introduces grangersearch, an R package for performing exhaustive Granger causality searches on multiple time series. The package provides: (1) exhaustive pairwise search across multiple variables, (2) automatic lag order optimization with visualization, (3) tidyverse-compatible syntax with pipe operators and non-standard evaluation, and (4) integration with the broom ecosystem through tidy() and glance() methods. The package wraps the vars infrastructure while providing a simple inter...

Submitted: January 4, 2026Subjects: Data Science; Data Science

Description / Details

This paper introduces grangersearch, an R package for performing exhaustive Granger causality searches on multiple time series. The package provides: (1) exhaustive pairwise search across multiple variables, (2) automatic lag order optimization with visualization, (3) tidyverse-compatible syntax with pipe operators and non-standard evaluation, and (4) integration with the broom ecosystem through tidy() and glance() methods. The package wraps the vars infrastructure while providing a simple interface for exploratory causal analysis. We describe the statistical methodology, demonstrate the package through worked examples, and discuss practical considerations for applied researchers.

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Date:
Jan 4, 2026
Topic:
Data Science
Area:
Data Science
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