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).
|Author||Jacolien van Rij [aut, cre], Martijn Wieling [aut], R. Harald Baayen [aut], Hedderik van Rijn [ctb]|
|Date of publication||2016-06-13 13:07:04|
|Maintainer||Jacolien van Rij <firstname.lastname@example.org>|
|License||GPL (>= 2)|
acf_n_plots: Generate N ACF plots of individual or aggregated time series.
acf_plot: Generate an ACF plot of an aggregated time series.
acf_resid: Generate an ACF plot of model residuals. Works for lm, lmer,...
check_resid: Inspect residuals of regression models.
compareML: Function for comparing two GAMM models.
convertNonAlphanumeric: Prepare string for regular expressions (backslash for all...
derive_timeseries: Derive the time series used in the AR1 model.
diagnostics: Visualization of the model fit for time series data.
diff_terms: Compare the formulas of two models and return the...
eeg: Raw EEG data, single trial, 50Hz.
fadeRug: Fade out the areas in a surface without data.
find_difference: Return the regions in which the smooth is significantly...
fvisgam: Visualization of nonlinear interactions, summed effects.
gamtabs: Convert model summary into Latex/HTML table for knitr/R...
get_coefs: Get coefficients for the parametric terms (intercepts and...
get_difference: Get model predictions for differences between conditions.
get_fitted: Get model all fitted values.
get_modelterm: Get estimated for selected model terms.
get_pca_predictions: Return PCA predictions.
get_predictions: Get model predictions for specific conditions.
get_random: Get coefficients for the random intercepts and random slopes.
info: Information on how to cite this package
infoMessages: Turn on or off information messages.
inspect_random: Inspection and interpretation of random factor smooths.
itsadug: Interpreting Time Series, Autocorrelated Data Using GAMMs...
missing_est: Return indices of data that were not fitted by the model.
plot_data: Visualization of the model fit for time series data.
plot_diff: Plot difference curve based on model predictions.
plot_diff2: Plot difference surface based on model predictions.
plot_modelfit: Visualization of the model fit for time series data.
plot_parametric: Visualization of group estimates.
plot_pca_surface: Visualization of the effect predictors in nonlinear...
plot_smooth: Visualization of smooths.
plot_topo: Visualization of EEG topo maps.
print_summary: Print a named list of strings, output from 'summary_data'.
pvisgam: Visualization of partial nonlinear interactions.
report_stats: Returns a description of the statistics of the smooth terms...
resid_gam: Extract model residuals and remove the autocorrelation...
rug_model: Add rug to plot, based on model.
simdat: Simulated time series data.
start_event: Determine the starting point for each time series.
start_value_rho: Extract the Lag 1 value from the ACF of the residuals of a...
summary_data: Print a descriptive summary of a data frame.
timeBins: Label timestamps as timebins of a given binsize.
wald_gam: Function for post-hoc comparison of the contrasts in a single...