animated_fixation_plot
                        Create GIF animation of fixations on a stimulus
                        images
aoi_test                Test whether a gaze coordinates are within or
                        outside a rectangular or elliptical AOI. The
                        aois df must contain the variables x0, x1, y0
                        and y1. x0 is the minimum x value, y0 the
                        minimum y value. x1 the maximum x value. y1 the
                        maximum y value and type where rect means that
                        the AOI is a rectangle and circle that the AOI
                        is a circle or ellipse If a column called name
                        is present, the output for each AOI will be
                        labelled accordingly. Otherwise, the output
                        will be labelled according to the order of the
                        AOI in the data frame. The df 'gaze' must
                        contain the variables onset, duration, x, and
                        y. Latency will be defined as the value in
                        onset of the first detected gaze coordinate in
                        the AOI Make sure that the timestamps are
                        correct! The function can be used with gaze
                        data either fixations, saccades, or single
                        samples. Note that the output variables are not
                        equally relevant for all types of gaze data.
                        For example, both total duration and latency
                        are relevant in many analyses focusing on
                        fixations, but total duration may be less
                        relevant in analyses of saccades.
cluster2m               Fixation detection by two-means clustering
downsample_gaze         Downsample gaze
draw_aois               Draw one or more areas of interest, AOIs, on a
                        stimulus image and save to the R prompt. The
                        input is the path to a 2D image. Supported file
                        formats: JPEG, BMP, PNG. The function returns a
                        data frame with all saved AOIs. By default,
                        AOIs are drawn in a coordinate system where y
                        is 0 in the lower extreme of the image, e.g.,
                        an ascending y axis. Tobii eye trackers use a
                        coordinate system with a descending y-axis,
                        e.g., x and y are 0 in the upper left corner of
                        the image. Make sure that your AOIS match the
                        coordinate system of your eye tracker output.
                        By setting the parameter reverse.y.axis to
                        TRUE, the saved AOIs will be reformatted to fit
                        a coordinate system with a descending y-axis.
                        All AOIS have the variables x0, x1, y0 and y1.
                        x0 is the minimum x value, y0 the minimum y
                        value. x1 the maximum x value. y1 the maximum y
                        value
filt_plot_2d            Plot fixation filtered vs. raw or unfiltered
                        gaze coordinates in 2D space.
filt_plot_temporal      Plot fixation filtered vs. raw gaze coordinates
find.transition.weights
                        Find transition weights for each sample in a
                        gaze matrix.
idt_filter              Dispersion-based fixation detection algorithm
                        '(I-DT)'
interpolate_with_margin
                        Interpolate over gaps (subsequent NAs) in
                        vector.
ivt_filter              I-VT algorithm for fixation and saccade
                        detection
kollaR                  Filtering, Visualization, and Analysis of Eye
                        Tracking Data
merge_adjacent_fixations
                        Merge adjacent fixations
plot_filter_results     Plot validity measures from one or more
                        fixation detection algorithms
plot_sample_velocity    Plot the sample-to-sample velocity of eye
                        tracking data.
plot_velocity_profiles
                        Create ggplot of saccade velocity profiles
process_gaze            Interpolation and smoothing of gaze-vector
sample.data.filtered    Fixation-filtered sample-by-sample example data
sample.data.fixation1   Fixations from 1 individual
sample.data.fixations   Fixations from 7 individuals
sample.data.processed   Pre-processed sample-by-sample example data
sample.data.saccades    Saccades from 3 individuals
sample.data.unprocessed
                        Unprocessed sample-by-sample example data
static_plot             Plot fixations in 2D space overlaied on a
                        stimulus image
