Package: tsoutliers 0.6-10
Javier López-de-Lacalle
tsoutliers: Detection of Outliers in Time Series
Detection of outliers in time series following the Chen and Liu (1993) <doi:10.2307/2290724> procedure. Innovational outliers, additive outliers, level shifts, temporary changes and seasonal level shifts are considered.
Authors:
tsoutliers_0.6-10.tar.gz
tsoutliers_0.6-10.tar.gz(r-4.5-noble)tsoutliers_0.6-10.tar.gz(r-4.4-noble)
tsoutliers_0.6-10.tgz(r-4.4-emscripten)tsoutliers_0.6-10.tgz(r-4.3-emscripten)
tsoutliers.pdf |tsoutliers.html✨
tsoutliers/json (API)
NEWS
# Install 'tsoutliers' in R: |
install.packages('tsoutliers', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 9 months agofrom:130b6315f4. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 10 2024 |
R-4.5-linux | OK | Oct 10 2024 |
Exports:calendar.effectscoefs2polydiscard.outliersfind.consecutive.outliersJarqueBera.testlocate.outlierslocate.outliers.ilooplocate.outliers.oloopoutliersoutliers.effectsoutliers.regressorsoutliers.tstatisticsplot.tsoutliersprint.tsoutliersremove.outlierstsotso0
Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo