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-any)DSFM_1.0.1.zip(r-4.6-any)DSFM_1.0.1.zip(r-4.5-any)
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 218 downloads 11 exports 18 dependencies

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

TargetResultTimeFilesSyslog
linux-develOK120
source / vignettesOK155
linux-releaseOK123
macos-releaseOK76
macos-oldrelOK84
windows-develOK77
windows-releaseOK76
windows-oldrelOK74
wasm-releaseOK105

Exports:calculate_errorsDFanPCDGaoPCDGulPCDPCDPPCDSPCfactor.testsSFMSOPCSPC

Dependencies:elasticnetGPArotationlarslatticemagrittrMASSMatrixmatrixcalcMatrixModelsmnormtnlmenumDerivpsychquantregsnSOPCSparseMsurvival