## Crime series identification

### Description

Performs crime series identification by finding the crime series that are most closely related (as measured by Bayes Factor) to an unsolved crime.

### Usage

seriesID(crime, solved, seriesData, varlist, estimateBF,
linkage.method = c("average", "single", "complete"), group.method = 3,
...)


### Arguments

 crime crime incident; vector of crime variables solved incident data for the solved crimes. Must have a column named crimeID. seriesData table of crimeIDs and crimeseries (results from makeSeriesData) varlist a list of the variable names (columns of solved and crime) used to create evidence variables with compareCrimes. estimateBF function to estimate the bayes factor from evidence variables linkage.method the type of linkage for comparing one crime to a set of crimes “average” uses the average bayes factor “single” uses the largest bayes factor (most similar) “complete” uses the smallest bayes factor (least similar) group.method the type of crime groups to form (see makeGroups for details) ... other arguments passed to compareCrimes

### Value

A list with two objects. score is a data.frame of the similarity scores for each element in solved. groups is the data.frame seriesData with an additional column indicating the crime group (using the method specified in group.method).

### References

Porter, M. D. (2014). A Statistical Approach to Crime Linkage. arXiv preprint arXiv:1410.2285.. http://arxiv.org/abs/1410.2285

### Examples

# See vignette: "Crime Series Identification and Clustering" for usage.