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itsadug (version 1.0.1)

Interpreting Time Series and Autocorrelated Data Using GAMMs

Description

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).

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Install

install.packages('itsadug')

Monthly Downloads

2,439

Version

1.0.1

License

GPL (>= 2)

Issues

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Pull Requests

0

Stars

2

Forks

1

Maintainer

Jacolien van Rij

Last Published

July 2nd, 2015

Functions in itsadug (1.0.1)

addInterval

Utility function.
diff_terms

Utility unction.
find_difference

Find the regions in which the smooth is significantly different from zero.
start_event

Determine the starting point for each time series.
dotplot_error

Utility function
missing_est

Utility unction.
gradientLegend

Utility function.
get_modelterm

Get estimated for selected model terms.
findAbsMin

Utility function.
horiz_error

Utility function.
simdat

Simulated time series data.
getCoords

Utility function.
se

Calculate standard error of the mean.
plotsurface

Creates a colored surface plot.
print_summary

Utility function.
errorBars

Utility function.
find_n_neighbors

Utility function.
get_difference

Get model predictions for differences between conditions.
info

Information on how to cite this package
plot_smooth

Visualization of smooths.
get_random

Get coefficients for the random intercepts and random slopes.
alphaPalette

Utility function.
alpha

Utility function.
check_normaldist

Compare distribution of data with normal distribution.
compareML

Function for comparing two GAMM models.
group_sort

Utility function.
acf_resid

Generate an ACF plot of model residuals. Works for lm, lmer, gam, bam, ....
check_resid

Inspect residuals of regression models.
get_predictions

Get model predictions for specific conditions.
acf_plot

Generate an ACF plot of an aggregated time series.
convertNonAlphanumeric

Utility unction.
eeg

Raw EEG data, single trial, 50Hz.
fvisgam

Visualization of nonlinear interactions.
infoMessages

Turn on or off information messages.
getCountData

Reducing fixations to count data.
inspect_random

Inspection of random factor smooths.
fill_area

Utility function
gamtabs

Convert the summary into a Latex table.
get_coefs

Get coefficients for the parametric terms (intercepts and random slopes).
acf_n_plots

Generate N ACF plots of individual or aggregated time series.
plot_topo

Visualization of EEG topo maps.
plot_diff2

Plot difference surface based on model predictions.
plot_error

Utility function
pvisgam

Visualization of nonlinear interactions.
plot_parametric

Visualization of group estimates.
timeBins

Defining timebins.
itsadug

Interpreting Time Series, Autocorrelated Data Using GAMMs (itsadug)
summary_data

Utility function.
emptyPlot

Utility function
move_n_point

Utility function.
plot_diff

Plot difference curve based on model predictions.
color_contour

Creates a contour plot with colored background.
countValues

Utility function.
getFigCoords

Get the figure region as coordinates of the current plot region.
fadeRug

Utility function.
resid_gam

Extract model residuals and remove the autocorrelation accounted for.