Package: deadband 0.1.0

deadband: Statistical Deadband Algorithms Comparison

Statistical deadband algorithms are based on the Send-On-Delta concept as in Miskowicz(2006,<doi:10.3390/s6010049>). A collection of functions compare effectiveness and fidelity of sampled signals using statistical deadband algorithms.

Authors:Nunzio Torrisi

deadband_0.1.0.tar.gz
deadband_0.1.0.zip(r-4.5)deadband_0.1.0.zip(r-4.4)deadband_0.1.0.zip(r-4.3)
deadband_0.1.0.tgz(r-4.4-any)deadband_0.1.0.tgz(r-4.3-any)
deadband_0.1.0.tar.gz(r-4.5-noble)deadband_0.1.0.tar.gz(r-4.4-noble)
deadband_0.1.0.tgz(r-4.4-emscripten)deadband_0.1.0.tgz(r-4.3-emscripten)
deadband.pdf |deadband.html
deadband/json (API)

# Install 'deadband' in R:
install.packages('deadband', repos = c('https://nunziotorrisi.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3 exports 0.00 score 5 dependencies 3 scripts 198 downloads

Last updated 8 years agofrom:ed8b5f0535. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 14 2024
R-4.5-winOKSep 14 2024
R-4.5-linuxOKSep 14 2024
R-4.4-winOKSep 14 2024
R-4.4-macOKSep 14 2024
R-4.3-winOKSep 14 2024
R-4.3-macOKSep 14 2024

Exports:deadbandADdeadbandBDdeadbandVD

Dependencies:curllatticeTTRxtszoo