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'))

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 254 downloads 8 exports 64 dependencies

Last updated 2 months agofrom:5cbec67915. Checks:OK: 1 NOTE: 1. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Oct 04 2024
R-4.5-linux-x86_64	NOTE	Oct 04 2024

Exports:augment join_empirical_hazard nobs plot_fit_on_data simulate_data survival_ln_mixture survival_ln_mixture_em tidy

Dependencies:abind backports bit bit64 broom checkmate cli clipr codetools colorspace cpp11 crayon distributional dplyr fansi farver generics ggplot2 globals glue gtable hardhat hms isoband labeling lattice lifecycle magrittr MASS Matrix matrixStats mgcv munsell nlme numDeriv parsnip pillar pkgconfig posterior prettyunits progress purrr R6 RColorBrewer Rcpp RcppArmadillo RcppGSL RcppParallel readr rlang scales stringi stringr survival tensorA tibble tidyr tidyselect tzdb utf8 vctrs viridisLite vroom withr