Package: DTSR 0.1.0
DTSR: Distributed Trimmed Scores Regression for Handling Missing Data
Provides functions for handling missing data using Distributed Trimmed Scores Regression and other imputation methods. It includes facilities for data imputation, evaluation metrics, and clustering analysis. It is designed to work in distributed computing environments to handle large datasets efficiently. The philosophy of the package is described in Guo G. (2024) <doi:10.1080/03610918.2022.2091779>.
Authors:
DTSR_0.1.0.tar.gz
DTSR_0.1.0.tar.gz(r-4.5-noble)DTSR_0.1.0.tar.gz(r-4.4-noble)
DTSR_0.1.0.tgz(r-4.4-emscripten)DTSR_0.1.0.tgz(r-4.3-emscripten)
DTSR.pdf |DTSR.html✨
DTSR/json (API)
# Install 'DTSR' in R: |
install.packages('DTSR', 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 2 months agofrom:b18b86c4e3. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 09 2024 |
R-4.5-linux | OK | Dec 09 2024 |
Exports:DEMDRPCADTSREMIndexCPPKNNmeanMLPCANIPALSRPCASVDSVDImputeTSR
Dependencies:abindbackportsbitbit64bootbroomcarcarDataclassclicliprclustercolorspacecowplotcpp11crayoncurlDBIDerivDMwR2doBydplyrfansifarverFormulagenericsggplot2gluegtablehmsisobandjsonlitelabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamnormtmodelrmomentsmunsellmvdalabnlmenloptrnnetnumDerivpbkrtestpenalizedpillarpkgconfigplyrprettyunitsprogresspurrrquantmodquantregR6RColorBrewerRcppRcppArmadilloRcppEigenreadrreshape2rlangrpartscalessnSparseMstringistringrsurvivaltibbletidyrtidyselectTTRtzdbutf8vctrsviridisLitevroomwithrxtszoo