Package: LFM 0.1.0

LFM: Laplace Factor Model Analysis and Evaluation

Enables the generation of Laplace factor models across diverse Laplace distributions and facilitates the application of Sparse Online Principal Component (SOPC), Incremental Principal Component (IPC), Parallel Principal Component (PPC), Sparse Approximate Principal Component (SAPC), Standard Principal Component (SPC), and Farm Test methods to these models. Evaluates the efficacy of these methods within the context of Laplace factor models by scrutinizing parameter estimation accuracy, mean square error, and the degree of sparsity.

Authors:Guangbao Guo [aut, cre], Siqi Liu [aut]

LFM_0.1.0.tar.gz
LFM_0.1.0.zip(r-4.5)LFM_0.1.0.zip(r-4.4)LFM_0.1.0.zip(r-4.3)
LFM_0.1.0.tgz(r-4.4-any)LFM_0.1.0.tgz(r-4.3-any)
LFM_0.1.0.tar.gz(r-4.5-noble)LFM_0.1.0.tar.gz(r-4.4-noble)
LFM_0.1.0.tgz(r-4.4-emscripten)LFM_0.1.0.tgz(r-4.3-emscripten)
LFM.pdf |LFM.html✨
LFM/json (API)

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

Peer review:

On CRAN:

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

1.00 score 1 scripts 7 exports 20 dependencies

Last updated 19 hours agofrom:aad9234818. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 20 2024
R-4.5-winOKNov 20 2024
R-4.5-linuxOKNov 20 2024
R-4.4-winOKNov 20 2024
R-4.4-macOKNov 20 2024
R-4.3-winOKNov 20 2024
R-4.3-macOKNov 20 2024

Exports:Ftest_LFMIPC_LFMLFMPPC_LFMSAPC_LFMSOPC_LFMSPC_LFM

Dependencies:clielasticnetFarmTestFuzzyNumbersFuzzyNumbers.Ext.2LaplacesDemonlarsmagrittrMASSmatrixcalcrbibutilsRcppRcppArmadilloRdpackrellipticalrlangRyacas0settingsSOPCxml2