Package: LPCM 0.47-6
LPCM: Local Principal Curve Methods
Fitting multivariate data patterns with local principal curves, including tools for data compression (projection) and measuring goodness-of-fit; with some additional functions for mean shift clustering. See Einbeck, Tutz and Evers (2005) <doi:10.1007/s11222-005-4073-8> and Ameijeiras-Alonso and Einbeck (2023) <doi:10.1007/s11634-023-00575-1>.
Authors:
LPCM_0.47-6.tar.gz
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LPCM.pdf |LPCM.html✨
LPCM/json (API)
NEWS
# Install 'LPCM' in R: |
install.packages('LPCM', repos = c('https://jeinbeck-code.r-universe.dev', 'https://cloud.r-project.org')) |
- calspeedflow - Speed-flow data from California.
- gaia - Gaia data
- gvessel - North Atlantic Water Temperature Data.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 months agofrom:1fbc8b6fa2. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 07 2024 |
R-4.5-win | OK | Nov 07 2024 |
R-4.5-linux | OK | Nov 07 2024 |
R-4.4-win | OK | Nov 07 2024 |
R-4.4-mac | OK | Nov 07 2024 |
R-4.3-win | OK | Nov 07 2024 |
R-4.3-mac | OK | Nov 07 2024 |
Exports:base.Rccoveragecoverage.rawdistancevectorenormfollowxkdexkernkerndlpclpc.controllpc.coveragelpc.curve.lengthlpc.fit.splinelpc.projectlpc.project.splinelpc.self.coveragelpc.splinelpc.spline.evallpc.splinefunmeanshiftmindistmsms.repms.rep.minms.self.coverageRcselect.self.coverageunscalevecdist
Dependencies: