Package: GLMMcosinor 0.2.1.9000

Rex Parsons

GLMMcosinor: Fit a Cosinor Model Using a Generalized Mixed Modeling Framework

Allows users to fit a cosinor model using the 'glmmTMB' framework. This extends on existing cosinor modeling packages, including 'cosinor' and 'circacompare', by including a wide range of available link functions and the capability to fit mixed models. The cosinor model is described by Cornelissen (2014) <doi:10.1186/1742-4682-11-16>.

Authors:Rex Parsons [aut, cre], Oliver Jayasinghe [aut], Nicole White [aut], Oliver Rawashdeh [aut, fnd], Prasad Chunduri [ctb, fnd], Margaret Doyle [ctb], Michael Sachs [rev], Joaquin Cavieres [rev]

GLMMcosinor_0.2.1.9000.tar.gz
GLMMcosinor_0.2.1.9000.zip(r-4.7)GLMMcosinor_0.2.1.9000.zip(r-4.6)GLMMcosinor_0.2.1.9000.zip(r-4.5)
GLMMcosinor_0.2.1.9000.tgz(r-4.6-any)GLMMcosinor_0.2.1.9000.tgz(r-4.5-any)
GLMMcosinor_0.2.1.9000.tar.gz(r-4.7-any)GLMMcosinor_0.2.1.9000.tar.gz(r-4.6-any)
GLMMcosinor_0.2.1.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
GLMMcosinor/json (API)

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

Reviews:rOpenSci Software Review #603

Bug tracker:https://github.com/ropensci/glmmcosinor/issues

Pkgdown/docs site:https://docs.ropensci.org

Datasets:
  • cosinor_mixed - Cosinor_mixed dataset for cosinor modeling examples.
  • vitamind - Vitamin D dataset for cosinor modeling examples.

On CRAN:

Conda:

6.01 score 3 stars 38 scripts 636 downloads 11 exports 71 dependencies

Last updated from:bc86b08db1 (on main). Checks:2 ERROR, 8 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64ERROR246
pkgdown docsOK237
source / vignettesOK291
linux-release-x86_64ERROR242
macos-release-arm64OK156
macos-oldrel-arm64OK168
windows-develOK160
windows-releaseOK167
windows-oldrelOK163
wasm-releaseOK176

Exports:amp_acroautoplotbellcglmmfit_model_and_processpolar_plotsigmasimulate_cosinortest_cosinor_componentstest_cosinor_levelsupdate_formula_and_data

Dependencies:assertthatbackportsbase64encbootbroomclicolorspacecowplotcpp11DerivdoBydplyrfarverforecastfracdiffgenericsggforceggplot2glmmTMBgluegtableisobandjsonlitelabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixmgcvmicrobenchmarkminqamodelrnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpolyclippurrrR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangS7sandwichscalesstringistringrsystemfontstibbletidyrtidyselecttimeDateTMBtweenrurcautf8vctrsviridisLitewithrzoo

GLMMcosinor
An brief introduction to the cosinor model | Introduction | cglmm() | A basic overview of cglmm() | Understanding the output | More advanced cglmm() model specification | Using summary() and testing for differences between estimates | Using predict() | Plotting cglmm objects | Large datasets | Assessing residual diagnostics of cglmm regression models using DHARMa | Differential rhythmicity | References
Rendered fromGLMMcosinor.Rmdusingknitr::rmarkdown

Last update: 2025-10-30
Started: 2023-02-08

Model specification
cglmm() | Using cglmm() | Specifying a single-component model with no grouping variable | Specifying a single-component model with a grouping variable and a shared MESOR | Specifying a single-component model with a grouping variable and an intercept (MESOR) | Specifying more complicated models using the amp_acro() function | Dispersion and zero-inflation model specification | Using summary(cglmm)
Rendered frommodel-specification.Rmdusingknitr::rmarkdown

Last update: 2025-10-30
Started: 2023-02-08

Visualizing models
Visualizing cglmm models | Polar plots
Rendered frommodel-visualizations.Rmdusingknitr::rmarkdown

Last update: 2025-10-30
Started: 2024-10-31

Mixed models
Data with subject-level differences | A single component model with random effects | REML
Rendered frommixed-models.Rmdusingknitr::rmarkdown

Last update: 2025-07-16
Started: 2023-02-08

Multicomponent cosinor modeling
Generating a two-component model | Generating a three-component model | Generating models with n-components
Rendered frommultiple-components.Rmdusingknitr::rmarkdown

Last update: 2024-10-31
Started: 2023-02-08

Simulating data
Simulating rhythmic data | Understanding the inputs for a simple model | Simulating grouped cosinor data | Simulating multi-component cosinor data
Rendered fromdata-simulations.Rmdusingknitr::rmarkdown

Last update: 2024-01-11
Started: 2023-02-08

Readme and manuals

Help Manual

Help pageTopics
Used to specify a cosinor component in the model formula.amp_acro
Process data for autoplotautoplot_data_processor
Plot a cosinor modelautoplot.cglmm
Fit cosinor model with '{glmmTMB}'cglmm
cosinor_mixed dataset for cosinor modeling examples.cosinor_mixed
Fit the cosinor GLMM model using the output from 'update_formula_and_data()' and a new formulafit_model_and_process
Create the background for a polar plot.get_background_grid
Add a ellipses layer to a polar plot.get_point_estimate_plot
Generates a polar plot with elliptical confidence intervalspolar_plot
Generates a polar plot with elliptical confidence intervalspolar_plot.cglmm
Predict from a cosinor modelpredict.cglmm
Print a brief summary of the 'cglmm' model.print.cglmm
Print test of modelprint.cglmmSubTest
Print the summary of a cosinor modelprint.cglmmSummary
Print results of test of cosinor modelprint.cglmmTest
Extract residual standard deviation or dispersion parametersigma.cglmm
Simulate data from a cosinor modelsimulate_cosinor
create a (sub) polar plot (iterated over for each component)sub_ggplot.cglmm.polar
Summarize a cosinor model Given a time variable and optional covariates, generate inference a cosinor fit. Gives estimates, confidence intervals, and tests for the raw parameters, and for the mean, amplitude, and acrophase parameters. If the model includes covariates, the function returns the estimates of the mean, amplitude, and acrophase for the group with covariates equal to 1 and equal to 0. This may not be the desired result for continuous covariates.summary.cglmm
Test for differences in a cosinor model between components.test_cosinor_components
Test for differences in a cosinor model between levels of the grouping variable.test_cosinor_levels
Update data and formula for fitting cglmm modelupdate_formula_and_data
Vitamin D dataset for cosinor modeling examples.vitamind