Space-Time Anomaly Detection using Scan Statistics
Set of increasing sets from left to right of input vector.
Find the connected sets for a location and its nearest neighbors.
Return those elements in the second set which are connected to those i...
Get the k nearest neighbors for each location, given its coordinates.
Convert a long data frame to a wide matrix.
Given a distance matrix, find the nearest neighbors.
Estimate baselines based on observed counts.
Estimate variances based on observed counts.
Estimate the parameters of a ZIP distribution.
Computes the flexibly shaped zones as in Tango (2005).
Flip a matrix upside down
Get indices of zero elements in a vector.
Extract a zone from the set of all zones.
Calculate the Gumbel -value for a scan statistic.
Is the relative error between two numbers is less than the given toler...
Return a set of the location and its neighbors if they are connected, ...
Returns TRUE if the neighboring locations are connected to the given l...
Find the increasing subsets of nearest neighbors for all locations...
Convert a matrix to a data frame.
Calculate the Monte Carlo -value for a scan statistic.
Permute the entries of the matrix, preserving row and column marginals...
Creates a set of all non-empty subsets of the integers from 1 to .
Print a scanstatistic object.
Run a scan statistic analysis.
Calculate the "Bayesian Spatial Scan Statistic" by Neill et al. (2006)...
Calculate the negative binomial bayesian scan statistic..
Calculate the expectation-based negative binomial scan statistic.
Calculate the expectation-based negative binomial scan statistic.
Calculate the expecation-based Poisson scan statistic.
Calculate the expectation-based Poisson scan statistic.
Calculate the highest-value EB ZIP loglihood ratio statistic.
Calculate the expectation-based ZIP scan statistic.
Calculate the space-time permutation scan statistic.
Calculate the population-based Poisson scan statistic.
Calculate the population-based Poisson scan statistic.
Calculate the space-time permutation scan statistic.
scanstatistics: Space-time anomaly detection using scan statistics.
Score each location over zones and duration.
Get the top (non-overlappig) clusters.
Detection of anomalous space-time clusters using the scan statistics methodology. Focuses on prospective surveillance of data streams, scanning for clusters with ongoing anomalies. Hypothesis testing is made possible by Monte Carlo simulation. Allévius (2018) <doi:10.21105/joss.00515>.
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