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TimeHiVE: Hierarchical Moving-Window Time Series Analysis Toolkit

Overview

TimeHiVE provides efficient R functions for hierarchical moving-window analysis of coupled time series data. The toolkit implements:

  • Parallel computation of Pearson and Mann-Kendall correlations
  • Optimized O(n log n) implementations of statistical tests
  • Customizable visualization of time-dependent relationships
  • Statistical significance testing with adjustable thresholds

Installation

You can install the development version from GitHub with:

# install.packages("remotes")
remotes::install_github("Ouroboro/TimeHiVE")

Usage

Basic Example 

library(TimeHiVE)

# Generate example data
set.seed(123)
series1 <- sin(seq(0, 4*pi, length.out = 200)) + rnorm(200, sd = 0.2)
series2 <- cos(seq(0, 4*pi, length.out = 200)) + rnorm(200, sd = 0.3)

# Perform analysis
results <- TH_coupled(
  series1 = series1,
  series2 = series2,
  m = 2,
  s = 6,
  alpha = 0.05,
  mode = "both"
)

# Visualize results
TH_plotc(results, mask = TRUE, mode = "both")

Main Functions

Documentation

For detailed documentation see:

?TH_coupled
?TH_plotc
?TH_MK_Corr
?TH_MK_Trend

Contributing

Contributions are welcome! Please follow these steps:

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/your-feature)
  3. Commit your changes (git commit -am 'Add some feature')
  4. Push to the branch (git push origin feature/your-feature)
  5. Open a Pull Request

License

This package is licensed under the GNU General Public License v3.0 (GPL-3.0). See the LICENSE file for details.

Contact

For questions or issues, please contact:

Vladimiro Andrea Boselli
Email:
GitHub: @Ouroboro