near_repeat_eval: Identification of Optimal Time and Distance Parameters for...

In rcrimeanalysis: An Implementation of Crime Analysis Methods

Identification of Optimal Time and Distance Parameters for Near Repeat Analysis

Description

This function performs an evaluation of given crime incidents to reccomend parameters for near repeat analysis. A series of time and distance parameters are tested using a full factorial design using the set of incident locations to determine the frequency of occurrence given each set of parameters. The results of the full factorial assessment are then modeled through interpolation and the second derivative is calculated to determine the inflection point. The inflection point represents the change in frequency of detected incidents which near repeat. Determination of the inflection point is completed for both the time and distance domains.

Usage

near_repeat_eval(data, epsg, tz = NULL)

Arguments

data	Data frame of crime or RMS data. See provided Chicago Data Portal example for reference
epsg	The EPSG Geodetic Parameter code for the area being considered. The EPSG code is used for identifying projections and performing coordinate transformations. If needed, the EPSG for an area can be found at https://spatialreference.org.
tz	Time zone for which the area being examined. By default this value is assigned as the same time zone of the system. For more information about time zones within R, see https://www.rdocumentation.org/packages/base/versions/3.6.1/topics/timezones.

Value

Returns a data frame with one instance (row) of two fields (columns). The fields are: distance and time. The instance indicates the optimal near repeat parameters for each. Note that distance is given in meters and time is given as days.

Author(s)

Jamie Spaulding, Keith Morris

Examples

data(crimes)
nr_dat <- subset(crimes, crimes$primary_type == "BURGLARY")
pars <- near_repeat_eval(data=nr_dat, tz="America/Chicago", epsg="32616")
pars

rcrimeanalysis documentation built on May 31, 2023, 8:54 p.m.