example_input_suspects_raw: Example input suspect data

In Sophie-c-h/gpsmartr: Geographic Profiling - Suspect Mapping And Ranking Technique (GP-SMART) in R

Example input suspect data

Description

A dataset containing an example set of suspect activity locations (nodes), in raw form. It includes the minimum information needed for the function fn_prepare_suspect_data() to operate. The example data are fictional; they were simulated based on the suspect activity location data used in Curtis-Ham et al (2022) to calibrate and test GP-SMART. The example data reflect the general location and distribution of the original data (in space, in time, per node type and per suspect). They do not represent the exact locations and times of suspects' activity locations in the original data. The simulation process meant that node and location types do not necessarily match the map location of the nodes. For example, a node with location type "residential" might fall on a commercial premises. In the original data, nodes with location type "residential" fall on residential premises.

Usage

data(example_input_suspects_raw)

Format

A data frame of 14826 row and 14 columns:

person_id

A unique reference number for the suspect. Can be a character or numeric vector.

death_date

Suspect's date of death if deceased. A date in format "YYYY-MM-DD"

x

Easting coordinate. Must be in metres to enable distance calculations.

y

Northing coordinate. Must be in metres to enable distance calculations.

node_category

The general category of the activity location. A character vector with values "span" or "event". Span and event nodes are treated differently when calculating activity node attributes.

node_type

The type of activity location. A factor with levels "home", "family_immediate", "family_ip", "family_other", "school", "work", "offence", "victim_witness", "incident", "police_other". Node type determines some activity node attribute values.

prior_offence_type

The type of offence, if it's an offence activity location and one of the crime types for which GP-SMART is currently calibrated. A factor with levels "burglary", "robbery" or "sex", being the crimes GP-SMART is calibrated for. Used for calculating behaviour similarity.

span_start_date

Start date of the activity location, if a span node. A date in format "YYYY-MM-DD".

span_end_date

End date of the activity location, if an event node. A date in format "YYYY-MM-DD".

event_start_date

Start date of the event, if an event node. A date in format "YYYY-MM-DD".

event_end_date

End date of the event, if an event node. A date in format "YYYY-MM-DD".

event_start_time

Start time of the event, if an event node. A difftime in format "HH:MM:SS". Time is not present for "police_other" event nodes.

event_end_time

End time of the event, if an event node. A difftime in format "HH:MM:SS". Time is not present for "police_other" event nodes.

location_type

The type of location in which the crime was committed. A factor with levels "residential", "commercial", "public", "street" or "unknown".

Source

Based on Offender activity location data provided by New Zealand Police.

References

Curtis-Ham S., Bernasco, W., Medvedev, O. N., & Polaschek, D. L. L (2022). 'A new geographic profiling method for mapping and ranking suspects in crime investigations: GP-SMART'. Journal of Investigative Psychology and Offender Profiling. https://doi.org/10.1002/jip.1585

Sophie-c-h/gpsmartr documentation built on April 13, 2022, 5:51 p.m.