caustests: Multiple Granger Causality Tests

Comprehensive suite of Granger causality tests for time series analysis, including:

  1. Toda-Yamamoto (1995) - Standard Granger causality robust to integration order
  2. Single Fourier Granger (Enders & Jones, 2016) - Captures smooth structural breaks
  3. Single Fourier Toda-Yamamoto (Nazlioglu et al., 2016) - Combines TY with Fourier
  4. Cumulative Fourier Granger (Enders & Jones, 2019) - Multiple Fourier frequencies
  5. Cumulative Fourier Toda-Yamamoto (Nazlioglu et al., 2019)
  6. Quantile Toda-Yamamoto (Cai et al., 2023) - Causality across quantiles
  7. Bootstrap Fourier Granger in Quantiles (Cheng et al., 2021) - BFGC-Q

All tests include bootstrap inference for robust p-values.

Installation

# Install from CRAN (when available)
install.packages("caustests")

# Or install development version from GitHub
# install.packages("devtools")
devtools::install_github("muhammedalkhalaf/caustests")

Usage

library(caustests)

# Load example data
data(caustests_data)

# Test 1: Toda-Yamamoto test
result1 <- caustests(caustests_data, test = 1, nboot = 999)
print(result1)

# Test 3: Single Fourier Toda-Yamamoto
result3 <- caustests(caustests_data, test = 3, kmax = 3, nboot = 999)
summary(result3)

# Test 6: Quantile causality
result6 <- caustests(caustests_data, test = 6, 
                     quantiles = c(0.1, 0.25, 0.5, 0.75, 0.9),
                     nboot = 999)
print(result6)
plot(result6)

References

Author

Dr. Merwan Roudane (merwanroudane920@gmail.com)

License

GPL-3