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Description

Use Time Series to Generate and Compare Power Spectral Density.

Functions that allow you to generate and compare power spectral density (PSD) plots given time series data. Fast Fourier Transform (FFT) is used to take a time series data, analyze the oscillations, and then output the frequencies of these oscillations in the time series in the form of a PSD plot.Thus given a time series, the dominant frequencies in the time series can be identified. Additional functions in this package allow the dominant frequencies of multiple groups of time series to be compared with each other. To see example usage with the main functions of this package, please visit this site: <https://yhhc2.github.io/psdr/articles/Introduction.html>. The mathematical operations used to generate the PSDs are described in these sites: <https://www.mathworks.com/help/matlab/ref/fft.html>. <https://www.mathworks.com/help/signal/ug/power-spectral-density-estimates-using-fft.html>.

psdr

R-CMD-check

Overview

Author: Yong-Han Hank Cheng

This package allows you to generate and compare power spectral density (PSD) plots given time series data. Fast Fourier Transform (FFT) is used to take a time series data, analyze the oscillations, and then output the frequencies of these oscillations in the time series in the form of a PSD plot.

Thus given a time series, the dominant frequencies in the time series can be identified. Additional functions in this package allow the dominant frequencies of multiple groups of time series to be compared with each other.

To see example usage with the main functions of this package, please visit this site: https://yhhc2.github.io/psdr/articles/Introduction.html

The mathematical operations used to generate the PSDs are described here:

“Fft.” Fast Fourier transform - MATLAB. Accessed May 25, 2021. https://www.mathworks.com/help/matlab/ref/fft.html.

“Signal Analyzer.” MATLAB & Simulink. Accessed May 25, 2021. https://www.mathworks.com/help/signal/ug/power-spectral-density-estimates-using-fft.html.

Installation

# Install the package from GitHub
devtools::install_github("yhhc2/psdr")
# Load package
library("psdr")

Usage

Source code: https://github.com/yhhc2/psdr

Visit the package’s website: https://yhhc2.github.io/psdr/

Visit this vignette for example usage: https://yhhc2.github.io/psdr/articles/Introduction.html

Visit this vignette for example output for each function usage: https://yhhc2.github.io/psdr/articles/Examples.html

License

The psdr package is licensed under the GPL (>=3) license. The logo is licensed under the CC BY 4.0 license.

Thanks

This package was developed in part during my time at the NIH as a postbac researcher. Acknowledgements to:

  • Kory Johnson and Yang Fann at the NINDS Bioinformatics Section for mentorship.

  • Jonathan Pomeraniec at the NIH Clinical Center for providing datasets to validate usage of package.

  • John Kakareka and Randy Pursley at the NIH CIT, Signal Processing and Instrumentation Section for guidance on signal processing.

  • Tianxia Wu at the NINDS Clinical Trials Unit for guidance on statistical testing.

  • NIH Undergraduate Scholarship Program and the NINDS Section of Infections of the Nervous System for supporting postbac.

Metadata

Version

1.0.1

License

Unknown

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