Package: flassomsm 0.1.0

flassomsm: Penalized Estimation for Multi-State Models with Lasso and Fused Penalties

Provides a suite of methods for detecting influential subjects in longitudinal datasets, particularly when observations occur at irregular time points. The methods identify individuals whose response trajectories deviate significantly from the population pattern, enabling detection of anomalies or subjects exerting undue influence on model outcomes.

Authors:Atanu Bhattacharjee [aut, cre, ctb], Gajendra Kumar Vishwakarma [aut, ctb], Abhipsa Tripathy [aut, ctb]

flassomsm_0.1.0.tar.gz
flassomsm_0.1.0.zip(r-4.7)flassomsm_0.1.0.zip(r-4.6)flassomsm_0.1.0.zip(r-4.5)
flassomsm_0.1.0.tgz(r-4.6-any)flassomsm_0.1.0.tgz(r-4.5-any)
flassomsm_0.1.0.tar.gz(r-4.7-any)flassomsm_0.1.0.tar.gz(r-4.6-any)
flassomsm_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
flassomsm/json (API)

# Install 'flassomsm' in R:
install.packages('flassomsm', repos = c('https://atanubhattacharjee.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 144 downloads 6 exports 44 dependencies

Last updated from:902194c3b6. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK150
source / vignettesOK185
linux-release-x86_64OK146
macos-release-arm64OK87
macos-oldrel-arm64OK98
windows-develOK103
windows-releaseOK103
windows-oldrelOK95
wasm-releaseOK99

Exports:covselecflassomsmflassomsm_admmflassomsm_pirlsprederrsimdata

Dependencies:clicodetoolscorpcorcrayondata.tabledigestdplyrforeachfuturefuture.applygenericsglmnetglobalsgluehmsiteratorslatticelifecyclelistenvmagrittrMatrixmstatenumDerivparallellypenalizedpillarpkgconfigprettyunitsprogressprogressrR6RColorBrewerRcppRcppArmadilloRcppEigenrlangshapesurvivaltibbletidyselectutf8vctrsviridisLitewithr