compareCrimes {crimelinkage}  R Documentation 
Calculates spatial and temporal distance, difference in categorical, and absolute value of numerical crime variables
compareCrimes(Pairs, crimedata, varlist, binary = TRUE, longlat = FALSE,
show.pb = FALSE, ...)
Pairs 
(n x 2) matrix of crimeIDs 
crimedata 
data.frame of crime incident data. There must be a column
named 
varlist 
a list with elements named: crimeID, spatial, temporal,
categorical, and numerical. Each element should be a vector of the column
names of

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