anisotropicsmoothing
Anisotropic smoothing for change-point regression data
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Anisotropic smoothing for change-point regression data
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README.md
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, Journal of Applied Statistics, 1–25.
For ease of usage, the methods for this paper have been coerced into the R package 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. 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. Advances in Statistical Climatology, Meteorology and Oceanography, 5(1), 57-66.
The micro-fire imagery data is available through a Github R package firedata. For any questions about data access or otherwise, please contact me at john.thompson@ubc.ca.
Owner
- Name: John R.J. Thompson
- Login: jrjthompson
- Kind: user
- Company: University of British Columbia Okanagan
- Repositories: 1
- Profile: https://github.com/jrjthompson
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: Thompson
given-names: John R.J.
orcid: https://orcid.org/0000-0002-6303-449X
title: "Anisotropic smoothing for change-point regression function estimation"
version: 1.0.0
identifiers:
- type: doi
value: 10.48550/arXiv.2012.00180
date-released: 2024-03-08