makeSeriesData: Make crime series data
In crimelinkage: Statistical Methods for Crime Series Linkage

Description Usage Arguments Details Value See Also Examples

Creates a data frame with index to crimedata and offender information. It is used to generate the linkage data.

1 2	makeSeriesData(crimedata, offenderTable, time = c("midpoint", "earliest", "latest"))

`crimedata`	data.frame of crime incident data. `crimedata` must have columns named: `crimeID`, `DT.FROM`, and `DT.TO`. Note: if crime timing is known exactly (uncensored) than only `DT.FROM` is required.
`offenderTable`	offender table that indicates the offender(s) responsible for solved crimes. `offenderTable` must have columns named: `offenderID` and `crimeID`.
`time`	the event time to be returned: 'midpoint', 'earliest', or 'latest'

The creates a crimeseries data object that is required for creating linkage data. It creates a crime series ID (CS) for every offender. Because of co-offending, a single crime (crimeID) can belong to multiple crime series.

data frame representation of the crime series present in the crimedata. It includes the crime ID (crimeID), index of that crimeID in the original crimedata (Index), the crime series ID (CS) corresponding to each offenderID, and the event time (TIME).

getCrimeSeries

data(crimes)
 data(offenders)

 seriesData = makeSeriesData(crimedata=crimes,offenderTable=offenders)
 head(seriesData)

 nCrimes = table(seriesData$offenderID)  # length of each crime series
 table(nCrimes)                  # distribution of crime series length
 mean(nCrimes>1)                 # proportion of offenders with multiple crimes

 nCO = table(seriesData$crimeID) # number of co-offenders per crime
 table(nCO)                      # distribution of number of co-offenders
 mean(nCO>1)                     # proportion of crimes with multiple co-offenders