Software

fdasrvf

I’m lead author of the fdasrvf R package (CRAN; GitHub).

This package performs alignment, PCA, and modeling of multidimensional and unidimensional functions using the square-root velocity framework (Srivastava et al., 2011 arXiv:1103.3817 and Tucker et al., 2013 doi:10.1016/j.csda.2012.12.001). This framework allows for elastic analysis of functional data through phase and amplitude separation. Multiple papers utilize the work in this package and is listed in the CRAN Functional Data Analysis Task View. See the package README for all the methods it implements and reference papers.

There are also version of this code for MATLAB, and Julia

Documentation for the Julia (Documentation: HTML)

fdasrsf

I’m lead author of the fdasrsf python package (PYPI; Conda; GitHub).

This package performs alignment, PCA, and modeling of multidimensional and unidimensional functions using the square-root velocity framework (Srivastava et al., 2011 arXiv:1103.3817 and Tucker et al., 2013 doi:10.1016/j.csda.2012.12.001). This framework allows for elastic analysis of functional data through phase and amplitude separation. Multiple papers utilize the work in this work and listed in the documentation. See the package README for all the methods it implements and reference papers.

Documentation for the Python (Documentation: HTML)

stpphawkes

I’m the lead author of the stpphawkes R package (CRAN;GitHub).

A R package for modeling of spatio-temporal and temporal point process using a Hawkes model accounting for missing data from the paper J. D. Tucker, L. Shand, and J. R. Lewis, “Handling Missing Data in Self-Exciting Point Process Models,” Spatial Statistics, vol. 29. pp. 160-176, 2019. PDF

veesa

I’m a devloper of the veesa R package (GitHub).

A R package for VEESA Pipeline for Explainable Machine Learning with Functional Data