Package: DSFM 1.0.1

DSFM: Distributed Skew Factor Model Estimation Methods

Provides a distributed framework for simulating and estimating skew factor models under various skewed and heavy-tailed distributions. The methods support distributed data generation, aggregation of local estimators, and evaluation of estimation performance via mean squared error, relative error, and sparsity measures. The distributed principal component (PC) estimators implemented in the package include 'IPC' (Independent Principal Component),'PPC' (Project Principal Component), 'SPC' (Sparse Principal Component), and other related distributed PC methods. The methodological background follows Guo G. (2023) <doi:10.1007/s00180-022-01270-z>.

Authors:Guangbao Guo [aut, cre], Yu Jin [aut]

DSFM_1.0.1.tar.gz
DSFM_1.0.1.zip(r-4.7)DSFM_1.0.1.zip(r-4.6)DSFM_1.0.1.zip(r-4.5)
DSFM_1.0.1.tgz(r-4.6-any)DSFM_1.0.1.tgz(r-4.5-any)
DSFM_1.0.1.tar.gz(r-4.7-any)DSFM_1.0.1.tar.gz(r-4.6-any)
DSFM_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
DSFM/json (API)

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

On CRAN:

Conda:

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

1.00 score 132 downloads 11 exports 18 dependencies

Last updated from:359a1e483b. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK122
source / vignettesOK168
linux-release-x86_64OK117
macos-release-arm64OK78
macos-oldrel-arm64OK97
windows-develOK91
windows-releaseOK84
windows-oldrelOK70
wasm-releaseOK96

Exports:calculate_errorsDFanPCDGaoPCDGulPCDPCDPPCDSPCfactor.testsSFMSOPCSPC

Dependencies:elasticnetGPArotationlarslatticemagrittrMASSMatrixmatrixcalcMatrixModelsmnormtnlmenumDerivpsychquantregsnSOPCSparseMsurvival