README.md

In capolitsch/trendfilteringSupp: Optimal one-dimensional data analysis with trend filtering

Installation

This package is now deprecated. Please use the trendfiltering R package instead.

Key references:

C. A. Politsch et al. (2020a). Trend Filtering – I. A modern statistical tool for time-domain astronomy and Astronomical Spectroscopy. Monthly Notices of the Royal Astronomical Society, 492(3), p. 4005-4018. [Link]

C. A. Politsch et al. (2020b). Trend Filtering – II. Denoising astronomical signals with varying degrees of smoothness. Monthly Notices of the Royal Astronomical Society, 492(3), p. 4019-4032. [Link]

R. J. Tibshirani (2014). Adaptive piecewise polynomial estimation via trend filtering. The Annals of Statistics, 42(1), p. 285-323. [Link]

A. Ramdas & R. J. Tibshirani (2016). Fast and Flexible ADMM Algorithms for Trend Filtering. Journal of Computational and Graphical Statistics, 25(3), p. 839-858. [Link]

T. B. Arnold, V. Sadhanala, and R. J. Tibshirani (2014). Fast algorithms for generalized lasso problems. glmgen R package, version 0.0.3. [Link]

capolitsch/trendfilteringSupp documentation built on Oct. 15, 2021, 11:04 a.m.