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-any)flassomsm_0.1.0.zip(r-4.6-any)flassomsm_0.1.0.zip(r-4.5-any)
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✨
DESCRIPTION
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 294 downloads 6 exports 44 dependencies

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

TargetResultTimeFilesSyslog
linux-develOK139
source / vignettesOK169
linux-releaseOK133
macos-releaseOK111
macos-oldrelOK91
windows-develOK109
windows-releaseOK97
windows-oldrelOK106
wasm-releaseOK98

Exports:covselecflassomsmflassomsm_admmflassomsm_pirlsprederrsimdata

Dependencies:clicodetoolscorpcorcrayondata.tabledigestdplyrforeachfuturefuture.applygenericsglmnetglobalsgluehmsiteratorslatticelifecyclelistenvmagrittrMatrixmstatenumDerivparallellypenalizedpillarpkgconfigprettyunitsprogressprogressrR6RColorBrewerRcppRcppArmadilloRcppEigenrlangshapesurvivaltibbletidyselectutf8vctrsviridisLitewithr