Learned Pattern Similarity (LPS) for time series, as described in Baydogan and Runger (2016) <doi:10.1007/s10618-015-0425-y>. Implements an approach to model the dependency structure in time series that generalizes the concept of autoregression to local auto-patterns. Generates a pattern-based representation of time series along with a similarity measure called Learned Pattern Similarity (LPS). Introduces a generalized autoregressive kernel. This package adapts C code from the 'randomForest' package by Andy Liaw and Matthew Wiener, itself based on original Fortran code by Leo Breiman and Adele Cutler.
| Version: | 1.1-0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | stats, graphics, grDevices, RColorBrewer |
| Published: | 2026-04-21 |
| DOI: | 10.32614/CRAN.package.LPStimeSeries |
| Author: | Mustafa Gokce Baydogan [aut, cre], Leo Breiman [ctb] (author of original Fortran code adapted in src/regTree.c), Adele Cutler [ctb] (co-author of original Fortran code), Andy Liaw [ctb] (author of 'randomForest' R port adapted here), Matthew Wiener [ctb] (co-author of 'randomForest' R port), Merck & Co., Inc. [cph] (copyright holder of adapted 'randomForest' C code) |
| Maintainer: | Mustafa Gokce Baydogan <baydoganmustafa at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| Citation: | LPStimeSeries citation info |
| Materials: | NEWS |
| CRAN checks: | LPStimeSeries results |
| Reference manual: | LPStimeSeries.html , LPStimeSeries.pdf |
| Package source: | LPStimeSeries_1.1-0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: LPStimeSeries_1.1-0.zip, r-oldrel: LPStimeSeries_1.1-0.zip |
| macOS binaries: | r-release (arm64): LPStimeSeries_1.1-0.tgz, r-oldrel (arm64): not available, r-release (x86_64): LPStimeSeries_1.1-0.tgz, r-oldrel (x86_64): LPStimeSeries_1.1-0.tgz |
| Old sources: | LPStimeSeries archive |
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