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nsp: Inference for Multiple Change-Points in Linear Models

Implementation of Narrowest Significance Pursuit, a general and flexible methodology for automatically detecting localised regions in data sequences which each must contain a change-point (understood as an abrupt change in the parameters of an underlying linear model), at a prescribed global significance level. Narrowest Significance Pursuit works with a wide range of distributional assumptions on the errors, and yields exact desired finite-sample coverage probabilities, regardless of the form or number of the covariates. For details, see P. Fryzlewicz (2021) <https://stats.lse.ac.uk/fryzlewicz/nsp/nsp.pdf>.

Version: 1.0.0
Depends: R (≥ 3.0.0)
Imports: lpSolve
Published: 2021-12-21
DOI: 10.32614/CRAN.package.nsp
Author: Piotr Fryzlewicz ORCID iD [aut, cre]
Maintainer: Piotr Fryzlewicz <p.fryzlewicz at lse.ac.uk>
License: GPL (≥ 3)
NeedsCompilation: no
CRAN checks: nsp results

Documentation:

Reference manual: nsp.pdf

Downloads:

Package source: nsp_1.0.0.tar.gz
Windows binaries: r-devel: nsp_1.0.0.zip, r-release: nsp_1.0.0.zip, r-oldrel: nsp_1.0.0.zip
macOS binaries: r-release (arm64): nsp_1.0.0.tgz, r-oldrel (arm64): nsp_1.0.0.tgz, r-release (x86_64): nsp_1.0.0.tgz, r-oldrel (x86_64): nsp_1.0.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=nsp to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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