Contains functions that help to determine event boundaries in event segmentation experiments by bootstrapping a critical segmentation magnitude under the null hypothesis that all key presses were randomly distributed across the experiment. Segmentation magnitude is defined as the sum of Gaussians centered at the times of the segmentation key presses performed by the participants. Within a participant, the maximum of the overlaid Gaussians is used to prevent an excessive influence of a single participant on the overall outcome (e.g. if a participant is pressing the key multiple times in succession). Further functions are included, such as plotting the results.
|Author||Frank Papenmeier [aut, cre], Konstantin Sering [ctb]|
|Date of publication||2016-08-11 18:40:42|
|Maintainer||Frank Papenmeier <firstname.lastname@example.org>|
|License||GPL (>= 3)|
bootstrap_critical_cutoffs: Bootstrap critical segmentation magnitude
flag_maxima_positions: Detect local maxima/minima of a numeric vector
get_eb_times: Retrieve event boundary times from a segmag object
get_eb_times_segmag_diff: Retrieve event boundary times for a difference of segmag...
plot.segmag: Plot segmentation magnitude
segmag: Create Segmentation Object