Package: ebmstate 0.1.5

ebmstate: Empirical Bayes Multi-State Cox Model

Implements an empirical Bayes, multi-state Cox model for survival analysis. Run "?'ebmstate-package'" for details. See also Schall (1991) <doi:10.1093/biomet/78.4.719>.

Authors:Rui Costa [aut, cre], Moritz Gerstung [aut], Terry M Therneau [ctb], Thomas Lumley [ctb], Hein Putter [ctb], Liesbeth de Wreede [ctb], Marta Fiocco [ctb], Ronald Geskus [ctb]

ebmstate_0.1.5.tar.gz
ebmstate_0.1.5.zip(r-4.5)ebmstate_0.1.5.zip(r-4.4)ebmstate_0.1.5.zip(r-4.3)
ebmstate_0.1.5.tgz(r-4.4-x86_64)ebmstate_0.1.5.tgz(r-4.4-arm64)ebmstate_0.1.5.tgz(r-4.3-x86_64)ebmstate_0.1.5.tgz(r-4.3-arm64)
ebmstate_0.1.5.tar.gz(r-4.5-noble)ebmstate_0.1.5.tar.gz(r-4.4-noble)
ebmstate_0.1.5.tgz(r-4.4-emscripten)ebmstate_0.1.5.tgz(r-4.3-emscripten)
ebmstate.pdf |ebmstate.html✨
ebmstate/json (API)

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

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

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

2.00 score 3 scripts 331 downloads 7 exports 10 dependencies

Last updated 1 months agofrom:c324038f15. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 19 2024
R-4.5-win-x86_64OKNov 19 2024
R-4.5-linux-x86_64OKNov 19 2024
R-4.4-win-x86_64OKNov 19 2024
R-4.4-mac-x86_64OKNov 19 2024
R-4.4-mac-aarch64OKNov 19 2024
R-4.3-win-x86_64OKNov 19 2024
R-4.3-mac-x86_64OKNov 19 2024
R-4.3-mac-aarch64OKNov 19 2024

Exports:boot_ebmstateCoxRFXloo_ebmstatemsfit_genericprobtrans_ebmstateprobtrans_fftprobtrans_mstate

Dependencies:data.tableHDIntervallatticeMatrixmstateRColorBrewerRcpprlangsurvivalviridisLite

Readme and manuals

Help Manual

Help pageTopics
Empirical Bayes multi-state Cox modelebmstate-package
Bootstrap confidence intervals for regression coefficientsboot_coxrfx
Bootstrap samples and bootstrap interval estimatesboot_ebmstate
Bootstrap confidence intervals for transition probabilitiesboot_probtrans
Ancillary function of 'boot_ebmstate'.CIs_for_target_state
Convolution function for clock-forward modelsconvolute_clockforward
Convolution function for clock-reset modelsconvolute_clockreset
Empirical Bayes, multi-state Cox modelCoxRFX
Example of an empirical Bayes model fitcoxrfx_object_sample
Spline approximations of the cumulative hazard functionscumhaz_splines
Ancillary function of 'boot_ebmstate'.cumhazCIs_for_target_transition
Ancillary function to 'boot_ebmstate'.extract_function
Compute the cumulative hazard of leaving a given statejoint_cum_hazard_function
Leave-one-out estimationloo_ebmstate
Convert factor to integer.MakeInteger
Compute subject-specific transition hazards.msfit_generic msfit_generic.coxrfx msfit_generic.default
Estimated cumulative hazard rates under an empirical Bayes Cox model (example)msfit_object_sample
An example of long-format multistate datamstate_data
A simulated event-history data setmstate_data_sample
Print method for CoxRFX objectsprint.coxrfx
Print method for 'msfit' objects generated by 'msfit_generic'print.msfit
Compute all transition probabilities from a given state using convolutionprobtrans_by_convolution
Compute transition probabilities under a clock-forward model using a convolution algorithm.probtrans_by_convolution_clockforward
Compute transition probabilities under a clock-reset model using a convolution algorithm.probtrans_by_convolution_clockreset
Compute subject-specific transition probabilities using convolution.probtrans_ebmstate
Compute subject-specific transition probabilities using a convolution algorithm based on the Fast Fourier transform.probtrans_fft
Compute subject-specific or overall transition probabilitiesprobtrans_mstate probtrans_mstate.coxrfx probtrans_mstate.default
Find the unique possible path until an absorbing statesuccessful_transitions
A summary method for CoxRFX modelssummary.coxrfx
Find all possible paths until absorption from a given starting stateunique_paths