Comprehensive suite of Granger causality tests for time series analysis, including:
All tests include bootstrap inference for robust p-values.
# Install from CRAN (when available)
install.packages("caustests")
# Or install development version from GitHub
# install.packages("devtools")
devtools::install_github("muhammedalkhalaf/caustests")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)Dr. Merwan Roudane (merwanroudane920@gmail.com)
GPL-3