https://github.com/jrjthompson/anisotropicsmoothing
Anisotropic smoothing for change-point regression data
https://github.com/jrjthompson/anisotropicsmoothing
anisotropic anisotropic-diffusion change-point fire-spread image-analysis image-processing kernel-regression kernels nonparametric nonparametric-regression regression smoothing
Last synced: 3 months ago
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Anisotropic smoothing for change-point regression data
- Host: GitHub
- URL: https://github.com/jrjthompson/anisotropicsmoothing
- Owner: jrjthompson
- Created: 2024-03-04T20:56:48.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-08-02T00:40:43.000Z (almost 2 years ago)
- Last Synced: 2025-09-04T21:06:56.596Z (9 months ago)
- Topics: anisotropic, anisotropic-diffusion, change-point, fire-spread, image-analysis, image-processing, kernel-regression, kernels, nonparametric, nonparametric-regression, regression, smoothing
- Language: Roff
- Homepage:
- Size: 2.95 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- Citation: CITATION.cff
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README
# Anisotropic Smoothing
This repo is code and methods for a general class of smoothing estimators for change-point regression functions. Articles associated with this work are:
- Thompson, J.R.J. (2024) [Iterative Smoothing for Change-point Regression Function Estimation](https://www.tandfonline.com/doi/full/10.1080/02664763.2024.2352759), *Journal of Applied Statistics*, 1–25.
For ease of usage, the methods for this paper have been coerced into the R package [nonsmooth](https://cran.rstudio.com/web/packages/nonsmooth/) through the function alc().
## Experimental fire spread data
The experimental fire data used in the article is associated with the following papers:
- Thompson, J.R.J., Wang, X.J., & Braun, W.J. (2020) [A mouse model for studying fire spread rates using experimental micro-fires](http://www.jenvstat.org/v09/i06). *Journal of Environmental Statistics*, 9(1), 1-19.
- Wang, X.J., Thompson, J.R.J., Braun, W.J., & Woolford, D.G. (2019) [Fitting a stochastic fire spread model to data.](https://ascmo.copernicus.org/articles/5/57/2019/) *Advances in Statistical Climatology, Meteorology and Oceanography*, 5(1), 57-66.
The micro-fire imagery data is available through a Github R package [firedata](https://github.com/jrjthompson/R-package-firedata). For any questions about data access or otherwise, please contact me at john.thompson@ubc.ca.