Package: FlexVarJM 0.1.0
Léonie Courcoul
FlexVarJM: Estimate Joint Models with Subject-Specific Variance
Estimation of mixed models including a subject-specific variance which can be time and covariate dependent. In the joint model framework, the package handles left truncation and allows a flexible dependence structure between the competing events and the longitudinal marker. The estimation is performed under the frequentist framework, using the Marquardt-Levenberg algorithm. (Courcoul, Tzourio, Woodward, Barbieri, Jacqmin-Gadda (2023) <arxiv:2306.16785>).
Authors:
FlexVarJM_0.1.0.tar.gz
FlexVarJM_0.1.0.tar.gz(r-4.5-noble)FlexVarJM_0.1.0.tar.gz(r-4.4-noble)
FlexVarJM_0.1.0.tgz(r-4.4-emscripten)FlexVarJM_0.1.0.tgz(r-4.3-emscripten)
FlexVarJM.pdf |FlexVarJM.html✨
FlexVarJM/json (API)
NEWS
# Install 'FlexVarJM' in R: |
install.packages('FlexVarJM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/leoniecourcoul/flexvarjm/issues
- Data_toy - Data_toy
Last updated 1 years agofrom:ae1340b859. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 15 2024 |
R-4.5-linux-x86_64 | OK | Dec 15 2024 |
Exports:goodness_of_fitlsjmlsmmpredyn
Dependencies:abindbackportsbootbroomcarcarDataclicodetoolscolorspacecommonmarkcorrplotcowplotcpp11curldata.tableDerivdoBydoParalleldplyrevaluateexactRankTestsfansifarverforeachFormulagenericsggplot2ggpubrggrepelggsciggsignifggtextgluegridExtragridtextgtablehighrisobanditeratorsjpegkm.ciKMsurvknitrlabelinglatticelcmmlifecyclelme4magrittrmarkdownmarqLevAlgMASSMatrixMatrixModelsmaxstatmgcvmicrobenchmarkminqamodelrmunsellmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpngpolynompurrrquantregR6randtoolboxRColorBrewerRcppRcppArmadilloRcppEigenrlangrngWELLrstatixscalesSparseMstringistringrsurvivalsurvminersurvMisctibbletidyrtidyselectutf8vctrsviridisLitewithrxfunxml2xtableyamlzoo
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Data_toy | Data_toy |
Initialisation of Survival Data at Gauss Kronrod time points | data.GaussKronrod |
Initialisation of Survival Data at Gauss Kronrod time points 2 | data.GaussKronrod2 |
Management of longitudinal data | data.manag.long |
Management of survival data | data.manag.surv |
Management of data for longitudinal submodel | data.time |
Gauss-Kronrod nodes and weights | gaussKronrod |
Predictions for the goodness of fit, of the random effects, the current value for each individuals and the cumulative hazard function for both events | goodness_of_fit |
Initialisation of Longitudinal Submodel | initial.long |
Log-likelihood computation | log_llh |
Log-likelihood computation in RCPP | log_llh_rcpp |
lsjm : Estimation of joint model for longitudinal data with a subject-specific time-dependent variability and time-to-event data. | lsjm |
lsmm : Estimation of location scale mixed model | lsmm |
Predictions computation | pred_s.t.bootstrap.tps |
Predictions computation | pred_s.t.ponctuel.tps |
Dynamic prediction for new individuals | predyn |