## Creates evidence variables by calculating ‘distance’ between crime pairs

### Description

Calculates spatial and temporal distance, difference in categorical, and absolute value of numerical crime variables

### Usage

compareCrimes(Pairs, crimedata, varlist, binary = TRUE, longlat = FALSE,
show.pb = FALSE, ...)


### Arguments

 Pairs (n x 2) matrix of crimeIDs crimedata data.frame of crime incident data. There must be a column named crimedata that refers to the crimeIDs given in Pairs. Other column names must correspond to what is given in varlist list. varlist a list with elements named: crimeID, spatial, temporal, categorical, and numerical. Each element should be a vector of the column names of crimedata corresponding to that feature: crimeID: crime ID for the crimedata that is matched to Pairs spatial: X,Y coordinates (in long,lat or Cartesian) of crimes temporal: DT.FROM, DT.TO of crimes. If times are uncensored, then only DT.FROM needs to be provided. categorical: (optional) categorical crime variables numerical: (optional) numerical crime variables binary (logical) match/no match or all combinations for categorical data longlat (logical) are spatial coordinates in (long,lat)? show.pb (logical) show the progress bar ... other arguments passed to hidden functions

### Value

data.frame of various proximity measures between the two crimes

• If spatial data is provided: the euclidean distance (if longlat = FALSE) or Haversine great circle distance (distHaversine if longlat = TRUE) is returned (in kilometers).

• If temporal data is provided: the expected absolute time difference is returned:

• temporal - overall difference (in days) [0,max]

• tod - time of day difference (in hours) [0,12]

• dow - fractional day of week difference (in days) [0,3.5]

• If categorical data is provided: if binary = TRUE then a 1 if the categories of each crime match and a 0 if they do not match. If binary = FALSE, then a factor of merged values (in form of f1:f2)

• If numerical data is provided: the absolute difference is returned.

### References

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

### Examples

data(crimes)
pairs = t(combn(crimes\$crimeID[1:4],m=2))   # make some crime pairs

varlist = list(
spatial = c("X", "Y"),
temporal = c("DT.FROM","DT.TO"),
categorical = c("MO1",  "MO2", "MO3"))    # crime variables list

compareCrimes(pairs,crimes,varlist,binary=TRUE)