Package: simglm 0.9.20
simglm: Simulate Models Based on the Generalized Linear Model
Simulates regression models, including both simple regression and generalized linear mixed models with up to three level of nesting. Power simulations that are flexible allowing the specification of missing data, unbalanced designs, and different random error distributions are built into the package.
Authors:
simglm_0.9.20.tar.gz
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simglm_0.9.20.tgz(r-4.5-any)simglm_0.9.20.tgz(r-4.4-any)simglm_0.9.20.tgz(r-4.3-any)
simglm_0.9.20.tar.gz(r-4.5-noble)simglm_0.9.20.tar.gz(r-4.4-noble)
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simglm.pdf |simglm.html✨
simglm/json (API)
NEWS
| # Install 'simglm' in R: |
| install.packages('simglm', repos = c('https://lebebr01.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/lebebr01/simglm/issues
Last updated 11 months agofrom:56e9a70ddf. Checks:1 OK, 8 NOTE. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 04 2025 |
| R-4.5-win | NOTE | Mar 04 2025 |
| R-4.5-mac | NOTE | Mar 04 2025 |
| R-4.5-linux | NOTE | Mar 04 2025 |
| R-4.4-win | NOTE | Mar 04 2025 |
| R-4.4-mac | NOTE | Mar 04 2025 |
| R-4.4-linux | NOTE | Mar 04 2025 |
| R-4.3-win | NOTE | Mar 04 2025 |
| R-4.3-mac | NOTE | Mar 04 2025 |
Exports:compute_density_valuescompute_statisticscorrelate_variablesdesireVardropout_missingextract_coefficientsgenerate_missinggenerate_responsemar_missingmissing_datamodel_fitparse_correlationparse_formulaparse_multiplememberparse_powerparse_randomeffectparse_varyargumentsparse_varyarguments_wrandom_missingrbimodreplicate_simulationrun_shinysim_continuous2sim_factor2sim_ordinal2sim_timesimglmsimulate_errorsimulate_fixedsimulate_heterogeneitysimulate_knotsimulate_randomeffecttransform_outcome
Dependencies:backportsbroomclicodetoolscpp11digestdplyrfansifuturefuture.applygenericsglobalsgluegtoolslifecyclelistenvmagrittrparallellypillarpkgconfigpurrrR6rlangstringistringrtibbletidyrtidyselectutf8vctrswithr
