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✨
DESCRIPTION
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 240 downloads 11 exports 18 dependencies

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

TargetResultTimeFilesSyslog
linux-devel-x86_64OK114
source / vignettesOK165
linux-release-x86_64OK119
macos-release-arm64OK88
macos-oldrel-arm64OK79
windows-develOK82
windows-releaseOK66
windows-oldrelOK71
wasm-releaseOK107

Exports:calculate_errorsDFanPCDGaoPCDGulPCDPCDPPCDSPCfactor.testsSFMSOPCSPC

Dependencies:elasticnetGPArotationlarslatticemagrittrMASSMatrixmatrixcalcMatrixModelsmnormtnlmenumDerivpsychquantregsnSOPCSparseMsurvival