Package: DTSR 0.1.0

Guangbao Guo

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:Guangbao Guo [aut, cre, cph], Ruiling Niu [aut]

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'))

Peer review:

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

1.00 score 516 downloads 13 exports 89 dependencies

Last updated 1 months agofrom:b18b86c4e3. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 09 2024
R-4.5-linuxOKDec 09 2024

Exports:DEMDRPCADTSREMIndexCPPKNNmeanMLPCANIPALSRPCASVDSVDImputeTSR

Dependencies:abindbackportsbitbit64bootbroomcarcarDataclassclicliprclustercolorspacecowplotcpp11crayoncurlDBIDerivDMwR2doBydplyrfansifarverFormulagenericsggplot2gluegtablehmsisobandjsonlitelabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamnormtmodelrmomentsmunsellmvdalabnlmenloptrnnetnumDerivpbkrtestpenalizedpillarpkgconfigplyrprettyunitsprogresspurrrquantmodquantregR6RColorBrewerRcppRcppArmadilloRcppEigenreadrreshape2rlangrpartscalessnSparseMstringistringrsurvivaltibbletidyrtidyselectTTRtzdbutf8vctrsviridisLitevroomwithrxtszoo