Package: lnmixsurv 3.1.6

Victor Hugo Soares Ney

lnmixsurv: Bayesian Mixture Log-Normal Survival Model

Bayesian Survival models via the mixture of Log-Normal distribution extends the well-known survival models and accommodates different behaviour over time and considers higher censored survival times. The proposal combines mixture distributions Fruhwirth-Schnatter(2006) <doi:10.1007/s11336-009-9121-4>, and data augmentation techniques Tanner and Wong (1987) <doi:10.1080/01621459.1987.10478458>.

Authors:Viviana das Graças Ribeiro Lobo [aut], Thaís Cristina Oliveira da Fonseca [aut], Mariane Branco Alves [aut], Vitor Capdeville [aut], Victor Hugo Soares Ney [cre]

lnmixsurv_3.1.6.tar.gz
lnmixsurv_3.1.6.tar.gz(r-4.5-noble)lnmixsurv_3.1.6.tar.gz(r-4.4-noble)
lnmixsurv.pdf |lnmixsurv.html✨
lnmixsurv/json (API)

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

Peer review:

Bug tracker:https://github.com/vivianalobo/lnmixsurv/issues

Uses libs:
  • gsl– GNU Scientific Library (GSL)
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • sim_data - Simulated lognormal mixture data.

3.65 score 18 scripts 106 downloads 8 exports 64 dependencies

Last updated 3 months agofrom:5cbec67915. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 03 2024
R-4.5-linux-x86_64NOTENov 03 2024

Exports:augmentjoin_empirical_hazardnobsplot_fit_on_datasimulate_datasurvival_ln_mixturesurvival_ln_mixture_emtidy

Dependencies:abindbackportsbitbit64broomcheckmateclicliprcodetoolscolorspacecpp11crayondistributionaldplyrfansifarvergenericsggplot2globalsgluegtablehardhathmsisobandlabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivparsnippillarpkgconfigposteriorprettyunitsprogresspurrrR6RColorBrewerRcppRcppArmadilloRcppGSLRcppParallelreadrrlangscalesstringistringrsurvivaltensorAtibbletidyrtidyselecttzdbutf8vctrsviridisLitevroomwithr

Comparison with other models

Rendered fromcompare.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2024-09-04
Started: 2024-09-04

Expectation Maximization

Rendered fromexpectation_maximization.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2024-09-04
Started: 2024-09-04

Get started

Rendered fromlnmixsurv.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2024-09-04
Started: 2024-09-04

Intercept only fits

Rendered fromintercept_only.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2024-09-04
Started: 2024-09-04

Parallel computation and posterior analysis

Rendered fromparallel_computation.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2024-09-04
Started: 2024-09-04