UCIDataLab/assocr: Quantify degreee of assocation between discrete event series

An implementation of the methods of <paper> in R. Contains methods for quantifying the degree of association between pairs of discrete event time series, focusing on the case where two associated event series exhibit temporal clustering such that the occurrence of one type of event at a particular time increases the likelihood that an event of the other type will also occur nearby in time. Multiple different score functions are used to quantify association, including characteristics of marked point processes and summary statistics for inter-event times. Two techniques are currently implemented for assessing the degree of associaton: (i) a population-based approach to calculate score-based likelihood ratios when a sample from a relevant population is available, and (ii) a resampling approach to compute coincidental match probabilities when only a single pair of event series is available.

install.packages("remotes")
remotes::install_github("UCIDataLab/assocr")