makePairs: Generates indices of linked and unlinked crime pairs (with...

In crimelinkage: Statistical Methods for Crime Series Linkage

Description

These functions generate a set of crimeIDs for linked and unlinked crime pairs. Linked pairs are assigned a weight according to how many crimes are in the crime series. For unlinked pairs, m crimes are selected from each crime group and pairs them with crimes in other crime groups.

Usage

makePairs(X, thres = 365, m = 40, show.pb = FALSE, seed = NULL)

makeLinked(X, thres = 365)

makeUnlinked(X, m, thres = 365, show.pb = FALSE, seed = NULL)

Arguments

X	crime series data (generated from makeSeriesData) with offender ID (offenderID), crime ID (crimeID), and the event datetime (TIME)
thres	the threshold (in days) of allowable time distance
m	the number of samples from each crime group (for unlinked pairs)
show.pb	(logical) should a progress bar be displayed
seed	seed for random number generation

Details

makePairs is a Convenience function that calls makeLinked and makeUnlinked and combines the results. It is unlikely that the latter two functions will need to be called directly.

For linked crime pairs, the weights are such that each crime series contributes a total weight of no greater than 1. Specifically, the weights are W_{ij} = \min \{1/N_m: V_i,V_j \in C_m \}, where C_m is the crime series for offender m and N_m is the number of crime pairs in their series (assuming V_i and V_j are together in at least one crime series). Due to co-offending, the sum of weights will be smaller than the number of series with at least two crimes.

To form the unlinked crime pairs, crime groups are identified as the maximal connected offender subgraphs. Then m indices are drawn from each crime group (with replacment) and paired with crimes from other crime groups according to weights that ensure that large groups don't give the most events.

Value

matrix of indices of crime pairs with weights. For makePairs, The last column type indicates if the crime pair is linked or unlinked.

Examples

data(crimes)
 data(offenders)
 seriesData = makeSeriesData(crimedata=crimes,offenderTable=offenders)
 allPairs = makePairs(seriesData,thres=365,m=40)

crimelinkage documentation built on May 2, 2019, 1:36 a.m.