| How to Obtain
Documents |
| |
|
|
NCJ Number:
|
NCJ 195167
|
|
Title:
|
Crime Hot Spot Forecasting: Modeling and Comparative Evaluation, Final Project Report
|
|
Author(s):
|
Wilpen Gorr ; Andreas Olligschlaeger
|
|
Date Published:
|
05/2002 |
|
Page Count:
|
61 |
|
Sponsoring Agency:
|
|
|
Grant Number:
|
98-IJ-CX-K005 |
|
Sale Source:
|
National Institute of Justice/NCJRS
Box 6000
Rockville, MD 20849
United States
NCJRS Photocopy Services
Box 6000
Rockville, MD 20849-6000
United States |
|
Document:
|
PDF |
|
Agency Summary:
|
Agency Summary |
|
Type:
|
Studies/research reports |
|
Language:
|
English |
|
Country:
|
United States |
|
Annotation:
|
This research investigated alternative methods for forecasting
major crimes one month ahead for fixed area units (precincts and
square grid cells) that comprise a jurisdiction. |
|
Abstract:
|
The study drew from research results in the field of forecasting,
which have provided a wealth of knowledge on forecast models and
experimental designs for comparing and assessing forecast
accuracy. The theoretical work which included specification of
forecast models, forecast performance measures, and experimental designs for evaluating crime forecasts yielded a crime
forecasting system of value to practitioners and researchers. A
case study of Pittsburgh, PA, yielded empirical findings. The
latter study concluded that for Part I violent crimes, the
leading indicator models are far superior to the univariate
method for large changes in crime patterns. The leading indicator
forecasts are analogous to high-quality leads on locations of
significant crime changes and warrant resource allocation. For
property crimes, the regression model is significantly better
than alternatives for forecasting large crime decreases, but the
neural network and univariate methods are best and not
significantly different for large increases. Similarly, the
neural network and regression models are equally useful for large
drug call decreases, but all three methods fail to perform well
for large increases. Improvement is needed in leading indicator
models for large increases in Part I property crimes and 911 drug
calls. Results for all other cases are good for the leading
indicator models. Future research that uses additional model
components, including fixed effects for demographic and land uses
that affect crime levels and additional lag structure for leading
indicator variables, will make major improvements in the
performance of these models. Based on this research, six
recommendations are offered for police, and four recommendations
are provided for researchers. 72 references, 13 tables, and 9
figures |
|
Main Term(s):
|
Community policing |
|
Index Term(s):
|
Mathematical models ; Police resource allocation ; Trend analysis ; Crime prediction ; Crime analysis ; Problem oriented policing ; NIJ final report ; Pennsylvania ; Crime Mapping |
|
Note:
|
For the executive summary of this report, see NCJ-195168. |
| |
To cite this abstract, use the following link:
https://www.ncjrs.gov/App/Publications/abstract.aspx?ID=195167
|
* A link to the full-text document is provided whenever possible. For documents
not available online, a link to the publisher's web site is provided.
|
|
Help | Contact Us | Home
