Package: itsadug 2.5

itsadug: Interpreting Time Series and Autocorrelated Data Using GAMMs

GAMM (Generalized Additive Mixed Modeling; Lin & Zhang, 1999) as implemented in the R package 'mgcv' (Wood, S.N., 2006; 2011) is a nonlinear regression analysis which is particularly useful for time course data such as EEG, pupil dilation, gaze data (eye tracking), and articulography recordings, but also for behavioral data such as reaction times and response data. As time course measures are sensitive to autocorrelation problems, GAMMs implements methods to reduce the autocorrelation problems. This package includes functions for the evaluation of GAMM models (e.g., model comparisons, determining regions of significance, inspection of autocorrelational structure in residuals) and interpreting of GAMMs (e.g., visualization of complex interactions, and contrasts).

Authors:Jacolien van Rij [aut, cre], Martijn Wieling [aut], R. Harald Baayen [aut], Hedderik van Rijn [ctb]

itsadug_2.5.tar.gz
itsadug_2.5.zip(r-4.7)itsadug_2.5.zip(r-4.6)itsadug_2.5.zip(r-4.5)
itsadug_2.5.tgz(r-4.6-any)itsadug_2.5.tgz(r-4.5-any)
itsadug_2.5.tar.gz(r-4.7-any)itsadug_2.5.tar.gz(r-4.6-any)
itsadug_2.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
itsadug/json (API)
NEWS

# Install 'itsadug' in R:
install.packages('itsadug', repos = c('https://jacolien.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • eeg - Raw EEG data, single trial, 50Hz.
  • simdat - Simulated time series data.

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

6.13 score 1 stars 744 scripts 4.5k downloads 20 mentions 48 exports 5 dependencies

Last updated from:6f9574d442. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK152
source / vignettesOK187
linux-release-x86_64OK149
macos-release-arm64OK153
macos-oldrel-arm64OK115
windows-develOK110
windows-releaseOK167
windows-oldrelOK108
wasm-releaseOK95

Exports:acf_n_plotsacf_plotacf_residcheck_residcompareMLconvertNonAlphanumericcorfitderive_timeseriesdiagnosticsdiff_termsdispersionfadeRugfind_differencefvisgamgamtabsget_coefsget_differenceget_fittedget_modeltermget_pca_predictionsget_predictionsget_randominfoinfoMessagesinspect_randommissing_estmodeledfobservationsplot_dataplot_diffplot_diff2plot_modelfitplot_parametricplot_pca_surfaceplot_smoothplot_topoprint_summarypvisgamrefLevelsreport_statsres_dfresid_gamrug_modelstart_eventstart_value_rhosummary_datatimeBinswald_gam

Dependencies:latticeMatrixmgcvnlmeplotfunctions

ACF: checking & handling autocorrelation

Jacolien van Rij

Rendered fromacf.Rmdusingknitr::rmarkdownon May 08 2026.

Last update: 2026-01-08
Started: 2015-07-02

Quick overview of plot functions

Jacolien van Rij

Rendered fromoverview.Rmdusingknitr::rmarkdownon May 08 2026.

Last update: 2020-04-29
Started: 2015-02-27

Testing for significance

Jacolien van Rij

Rendered fromtest.Rmdusingknitr::rmarkdownon May 08 2026.

Last update: 2026-01-08
Started: 2016-03-20

Visual inspection of GAMM models

Jacolien van Rij

Rendered frominspect.Rmdusingknitr::rmarkdownon May 08 2026.

Last update: 2026-01-08
Started: 2016-03-20

Readme and manuals

Help Manual

Help pageTopics
Generate N ACF plots of individual or aggregated time series.acf_n_plots
Generate an ACF plot of an aggregated time series.acf_plot
Generate an ACF plot of model residuals. Works for lm, lmer, gam, bam, ....acf_resid
Inspect residuals of regression models.check_resid
Function for comparing two GAMM models.compareML
Prepare string for regular expressions (backslash for all non-letter and non-digit characters)convertNonAlphanumeric
Calculate the correlation between the fitted model and data.corfit
Derive the time series used in the AR1 model.derive_timeseries
Visualization of the model fit for time series data.diagnostics
Compare the formulas of two models and return the difference(s).diff_terms
Calculate the dispersion of the residualsdispersion
Raw EEG data, single trial, 50Hz.eeg
Fade out the areas in a surface without data.fadeRug
Return the regions in which the smooth is significantly different from zero.find_difference
Visualization of nonlinear interactions, summed effects.fvisgam
Convert model summary into Latex/HTML table for knitr/R Markdown reports.gamtabs
Get coefficients for the parametric terms (intercepts and random slopes).get_coefs
Get model predictions for differences between conditions.get_difference
Get model all fitted values.get_fitted
Get estimated for selected model terms.get_modelterm
Return PCA predictions.get_pca_predictions
Get model predictions for specific conditions.get_predictions
Get coefficients for the random intercepts and random slopes.get_random
Information on how to cite this packageinfo
Turn on or off information messages.infoMessages
Inspection and interpretation of random factor smooths.inspect_random
Return indices of data that were not fitted by the model.missing_est
Retrieve the degrees of freedom specified in the model.modeledf
Number of observations in the model.observations
Visualization of the model fit for time series data.plot_data
Plot difference curve based on model predictions.plotDiff plot_diff
Plot difference surface based on model predictions.plotDiff2D plot_diff2
Visualization of the model fit for time series data.plot_modelfit
Visualization of group estimates.plot_parametric
Visualization of the effect predictors in nonlinear interactions with principled components.plot_pca_surface
Visualization of smooths.plot_smooth
Visualization of EEG topo maps.plot_topo
Print a named list of strings, output from 'summary_data'.print_summary
Visualization of partial nonlinear interactions.pvisgam
Return a list with reference levels for each factor.refLevels
Returns a description of the statistics of the smooth terms for reporting.report_stats
Retrieve the residual degrees of freedom from the model.res_df
Extract model residuals and remove the autocorrelation accounted for.resid.gam resid_gam
Add rug to plot, based on model.rug_model
Simulated time series data.simdat
Determine the starting point for each time series.start_event
Extract the Lag 1 value from the ACF of the residuals of a gam, bam, lm, lmer model, ...start_value_rho
Print a descriptive summary of a data frame.summary_data
Label timestamps as timebins of a given binsize.timeBins
Function for post-hoc comparison of the contrasts in a single GAMM model.wald_gam