Package: inlamemi 1.0.0
Emma Skarstein
inlamemi: Missing Data and Measurement Error Modelling in INLA
Facilitates fitting measurement error and missing data imputation models using integrated nested Laplace approximations, according to the method described in Skarstein, Martino and Muff (2023) <doi:10.1002/bimj.202300078>. See Skarstein and Muff (2024) <doi:10.48550/arXiv.2406.08172> for details on using the package.
Authors:
inlamemi_1.0.0.tar.gz
inlamemi_1.0.0.tar.gz(r-4.5-noble)inlamemi_1.0.0.tar.gz(r-4.4-noble)
inlamemi_1.0.0.tgz(r-4.4-emscripten)inlamemi_1.0.0.tgz(r-4.3-emscripten)
inlamemi.pdf |inlamemi.html✨
inlamemi/json (API)
NEWS
| # Install 'inlamemi' in R: |
| install.packages('inlamemi', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/emmaskarstein/inlamemi/issues
- framingham - Framingham heart study data
- mar_data - Simulated data with observation missing at random
- nhanes_survival - Survival data with repeated systolic blood pressure measurements
- simple_data - Simple simulated data
- two_error_data - Simulated data with two covariates with classical measurement error
Last updated 3 months agofrom:eb6616b919. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 23 2024 |
| R-4.5-linux | OK | Sep 23 2024 |
Exports:extract_variables_from_formulafit_inlamemimake_inlamemi_control.familymake_inlamemi_familiesmake_inlamemi_formulamake_inlamemi_scaling_vectormake_inlamemi_stacksshow_data_structure
Dependencies:clicolorspacedplyrfansifarvergenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbletidyselectutf8vctrsviridisLitewithr
How are the models structured?
Rendered fromVisualize_model_structure.Rmdusingknitr::rmarkdownon Sep 23 2024.Last update: 2024-06-25
Started: 2024-06-25
How to not use inlamemi
Rendered fromhow_to_not_use_inlamemi.Rmdusingknitr::rmarkdownon Sep 23 2024.Last update: 2024-06-25
Started: 2024-06-25
Influence of systolic blood pressure on coronary heart disease
Rendered fromFramingham_heart_study.Rmdusingknitr::rmarkdownon Sep 23 2024.Last update: 2024-06-25
Started: 2024-06-25
Modifying the default plot
Rendered frommodifying_default_plot.Rmdusingknitr::rmarkdownon Sep 23 2024.Last update: 2024-06-25
Started: 2024-06-25
Multiple variables with measurement error and missingness
Rendered frommultiple_error_variables.Rmdusingknitr::rmarkdownon Sep 23 2024.Last update: 2024-06-25
Started: 2024-06-25
Simulated examples
Rendered fromsimulated_examples.Rmdusingknitr::rmarkdownon Sep 23 2024.Last update: 2024-06-25
Started: 2024-06-25
Survival data with repeated systolic blood pressure measurements
Rendered fromnhanes_survival.Rmdusingknitr::rmarkdownon Sep 23 2024.Last update: 2024-06-25
Started: 2024-06-25
