Package: tramME 1.0.4
tramME: Transformation Models with Mixed Effects
Likelihood-based estimation of mixed-effects transformation models using the Template Model Builder ('TMB', Kristensen et al., 2016) <doi:10.18637/jss.v070.i05>. The technical details of transformation models are given in Hothorn et al. (2018) <doi:10.1111/sjos.12291>. Likelihood contributions of exact, randomly censored (left, right, interval) and truncated observations are supported. The random effects are assumed to be normally distributed on the scale of the transformation function, the marginal likelihood is evaluated using the Laplace approximation, and the gradients are calculated with automatic differentiation (Tamasi & Hothorn, 2021) <doi:10.32614/RJ-2021-075>. Penalized smooth shift terms can be defined using 'mgcv'.
Authors:
tramME_1.0.4.tar.gz
tramME_1.0.4.zip(r-4.5)tramME_1.0.4.zip(r-4.4)
tramME_1.0.4.tgz(r-4.4-x86_64)tramME_1.0.4.tgz(r-4.4-arm64)
tramME_1.0.4.tar.gz(r-4.5-noble)tramME_1.0.4.tar.gz(r-4.4-noble)
tramME_1.0.4.tgz(r-4.4-emscripten)
tramME.pdf |tramME.html✨
tramME/json (API)
NEWS
# Install 'tramME' in R: |
install.packages('tramME', repos = c('https://r-forge.r-universe.dev', 'https://cloud.r-project.org')) |
The latest version of this package failed to build. Look at thebuild logs for more information.
Bug tracker:https://r-forge.r-project.org/projects/ctm
Last updated 1 months agofrom:8a7cbb914a. Checks:OK: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 18 2024 |
R-4.5-win-x86_64 | OK | Nov 11 2024 |
R-4.5-linux-x86_64 | OK | Nov 08 2024 |
R-4.4-win-x86_64 | OK | Nov 18 2024 |
R-4.4-mac-x86_64 | OK | Nov 18 2024 |
R-4.4-mac-aarch64 | OK | Nov 18 2024 |
Exports:.tramME2ctmBoxCoxMEColrMECoxphMEduplicateedf_smoothLehmannMELmMEoptim_controlPolrMEranefRespsmooth_termsSurvregMEtramMEtramME_modeltramTMBVarCorrvarcovvarcov<-
Dependencies:alabamabasefunBBbootcodetoolsconeprojFormulalatticelme4MASSMatrixmgcvminqamltmultcompmvtnormnlmenloptrnumDerivorthopolynompolynomquadprogRcppRcppArmadilloRcppEigensandwichsurvivalTH.dataTMBtramvariableszoo