Interpreting Time Series and Autocorrelated Data Using GAMMs

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Documentation for package ‘itsadug’ version 2.4.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

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, gam, bam, ....
check_resid	Inspect residuals of regression models.
compareML	Function for comparing two GAMM models.
convertNonAlphanumeric	Prepare string for regular expressions (backslash for all non-letter and non-digit characters)
corfit	Calculate the correlation between the fitted model and data.
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 difference(s).
dispersion	Calculate the dispersion of the residuals
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 different from zero.
fvisgam	Visualization of nonlinear interactions, summed effects.
gamtabs	Convert model summary into Latex/HTML table for knitr/R Markdown reports.
get_coefs	Get coefficients for the parametric terms (intercepts and random slopes).
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 (itsadug)
missing_est	Return indices of data that were not fitted by the model.
modeledf	Retrieve the degrees of freedom specified in the model.
observations	Number of observations in the model.
plotDiff	Plot difference curve based on model predictions.
plotDiff2D	Plot difference surface based on model predictions.
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 interactions with principled components.
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.
refLevels	Return a list with reference levels for each factor.
report_stats	Returns a description of the statistics of the smooth terms for reporting.
resid.gam	Extract model residuals and remove the autocorrelation accounted for.
resid_gam	Extract model residuals and remove the autocorrelation accounted for.
res_df	Retrieve the residual degrees of freedom from the model.
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 gam, bam, lm, lmer model, ...
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 GAMM model.