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).
News
itsadug 2.3
Changes in arguments:
plot_diff/ plot_diff2: the arguments 'plotCI' and 'f' are replaced by 'se' for consistency with plot_smooth, fvisgam, pvisgam
pvisgam: argument 'type' deleted, because it was not used anymore
plot_smooths: argument 'sim.ci' allows to choose for simulataneous CI error bars (see get_predictions)
pvisgam, fvisgam, plot_diff2: the argument 'show.diff' indicates the area(s) in the surface that are significantly different from zero (i.e., that do not include zero in the confidence intervals). Note: This is just meant as a rough indication, and the user should be careful with the interpretation.
Minor changes:
pvisgam, fvisgam: if main is not specified, the name of the dependent variable is printed as title.
Bug fixes:
get_predictions: changing multiple column output to single column output to avoid problems with tidyverse usage (request from Joseph Fruehwald).
itsadug 2.2.5
Bug fixes:
get_coefs: now also works with only 1 parametric term
plot_topo: allows to change size when the new parameter setmargin is set to false.
New features:
plot_diff2: argument show.diff to show where the surface is not different from zero
Minor changes:
get_predictions: output should work now with tidyverse packages
compareML: minor changes in output compareML, e.g. "Difference" instead of "Chisq" as header in the table, and above the table a summary is mentioned in all cases.
plot_diff2: argument color does now also accept a vector of colors that will define a custom gradient palette.
plot_diff: argument col.diff to change color of significant region
pvisgam: se=1 also works for contour plots. To do: this functions need reimplementation for more efficient maintenance.
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itsadug 2.2.4
Minor changes:
compareML: replaced warning for use of AIC by information message
itsadug 2.2.3
Minor changes:
plot_smooth now allows to select more than one value for predictors in argument cond. This makes it possible to use plot_all for plotting only a subset of the data.
itsadug 2.2.2
Minor changes:
plot_smooth now also works for binomial predictors
get_modelterms now also works for binomial predictors
itsadug 2.2.1
Bug fix:
fixed bug in plot_smooth: plot_all line specifics (lwd, lty), but changed colors instead. Bug fixed.
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itsadug 2.2
Bug fixes:
fixed bug in plot_smooth: plot_all didn't plot colors or line specifics (lwd, lty), bug fixed and automatically colored lines are plotted for each level.
fixed bug in plot_diff: error in plot_diff when writing the estimated differences to the terminal, bug now fixed.
Minor change:
function fadeRug reimplemented, now based on mgcv's exclude.too.far function.
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itsadug 2.1
Major changes:
The package 'itsadug' has been split into two: all general multipurpose plot functions have been moved to the new package 'plotfunctions', whereas 'itsadug' now contains only the functions specialized for (nonlinear) regression models and autocorrelation problems.
Bug fixes:
fixed mark.diff error for nonsignificant differences
fixed bug in plot_smooth: using 'fit' as predictor will cause an
interpretable error message instead of not plotting
fixed bug in plot_smooth: lty and lwd can be set for the different levels of
plot_all.
fixed bug in plot_modelfit: can also be used for binomial count data
(only with logit link)
Other:
by installing the package data.table, start_event will run much faster
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itsadug 2.0
Major changes:
a. Vignettes:
New vignettes. Setup as short tutorials, which also introduce useful functions. Currently three included, about inspection of the model, testing for significance, and checking for autocorrelation. See also help(itsadug) for an overview.
a. New functions:
plot_modelfit: plotting the model fit and data for n randomly selected time series
plot_data (thanks to Tino Sering): plot observations on which model is based
check_resid newly implemented: check distribution of residuals and autocorrelation
diagnostics: inspect trends in residuals and distributions of predictors
plot_image: add image to plot region or as background
get_pca_predictions: extract the effect of a predictor that was included as part of a principle component
plot_pca_surface: plot surface of a principle component predictors in GAMMs
get_fitted: return fitted values, with or with random effects
wald_gam: nonparametric test for categorical predictors
start_value_rho: determine a start value for rho, which need to be finetuned
derive_timeseries: derive time series from AR.start info in the model
marginDensityPlot: add distribution of predictor in the margins of a plot
b. Bugs fixed:
fixed bug in acf_resid: errors that appeared with missing data should be fixed
fixed bug in fvisgam: too.far reimplemented
fixed bug in plot_smooth: with col=NULL no line was plotted, now with col=NULL a black line is plotted
fixed bug in check_normaldist: now it also works with binomial distribution (automatically centered)