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Using an approach based on similarity graph to estimate change-point(s) and the corresponding p-values. Can be applied to any type of data (high-dimensional, non-Euclidean, etc.) as long as a reasonable similarity measure is available.
| Version: | 1.0 |
| Depends: | R (≥ 3.0.1) |
| Suggests: | ade4 |
| Published: | 2020-09-24 |
| Author: | Hao Chen, Nancy R. Zhang, Lynna Chu, and Hoseung Song |
| Maintainer: | Hao Chen <hxchen at ucdavis.edu> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | gSeg results |
| Reference manual: | gSeg.pdf |
| Package source: | gSeg_1.0.tar.gz |
| Windows binaries: | r-devel: gSeg_1.0.zip, r-release: gSeg_1.0.zip, r-oldrel: gSeg_1.0.zip |
| macOS binaries: | r-release (arm64): gSeg_1.0.tgz, r-oldrel (arm64): gSeg_1.0.tgz, r-release (x86_64): gSeg_1.0.tgz, r-oldrel (x86_64): gSeg_1.0.tgz |
| Old sources: | gSeg archive |
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