Package: EEMDelm 0.1.1
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Girish Kumar Jha
EEMDelm: Ensemble Empirical Mode Decomposition and Its Variant Based ELM Model
Forecasting univariate time series with different decomposition based Extreme Learning Machine models. For method details see Yu L, Wang S, Lai KK (2008). <doi:10.1016/j.eneco.2008.05.003>, Parida M, Behera MK, Nayak N (2018). <doi:10.1109/ICSESP.2018.8376723>.
Authors:
EEMDelm_0.1.1.tar.gz
EEMDelm_0.1.1.tar.gz(r-4.5-noble)EEMDelm_0.1.1.tar.gz(r-4.4-noble)
EEMDelm_0.1.1.tgz(r-4.4-emscripten)EEMDelm_0.1.1.tgz(r-4.3-emscripten)
EEMDelm.pdf |EEMDelm.html✨
EEMDelm/json (API)
# Install 'EEMDelm' in R: |
install.packages('EEMDelm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- Data_Soybean - Monthly International Soybean Oil Price
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:8ea0bdc4ac. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Sep 03 2024 |
R-4.5-linux | OK | Sep 03 2024 |
Exports:CEEMDANelmEEMDELMEMDelm
Dependencies:askpassclicodetoolscolorspacecurlDerivfansifarverforeachforecastfracdiffgenericsggplot2glmnetgluegreyboxgtablehttrisobanditeratorsjsonlitelabelinglatticelifecyclelmtestmagrittrMAPAMASSMatrixmgcvmimemunsellneuralnetnlmenloptrnnetnnforopensslpillarpkgconfigplotrixpracmaquadprogquantmodR6RColorBrewerRcppRcppArmadilloRcppEigenrlangRlibeemdscalesshapesmoothstatmodsurvivalsystexregtibbletimeDatetseriestsutilsTTRurcaurootutf8vctrsviridisLitewithrxtablextszoo