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itsadug  

Interpreting Time Series and Autocorrelated Data Using GAMMs
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Download and install itsadug package within the R console
Install from CRAN:
install.packages("itsadug")

Install from Github:
library("remotes")
install_github("cran/itsadug")

Install by package version:
library("remotes")
install_version("itsadug", "2.4.1")



Attach the package and use:
library("itsadug")
Maintained by
Jacolien van Rij
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-02-27
Latest Update: 2022-06-17
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).
How to cite:
Jacolien van Rij (2015). itsadug: Interpreting Time Series and Autocorrelated Data Using GAMMs. R package version 2.4.1, https://cran.r-project.org/web/packages/itsadug. Accessed 28 Jan. 2025.
Previous versions and publish date:
0.8 (2015-02-27 06:57), 1.0.1 (2015-07-02 13:42), 2.0 (2016-03-20 16:27), 2.1 (2016-05-28 15:52), 2.2 (2016-06-13 13:07), 2.3 (2017-08-31 16:42), 2.4 (2020-04-29 12:40)
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