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Mapping & Analysis for Public Safety Program | NACJD GIS Resources | CrimeStat III Training
Download All Files (ZIP 46.9MB) (Updated 2007-03-26)
UPDATED March 2007
CrimeStat Program (version 3.1) (ZIP 811K)
General sample data set (ZIP 46K)
Sample data set for journey to crime module (ZIP 106K)
Sample data sets for Bayesian Journey to Crime module (ZIP 2.2M) New (2007-03-21)
Sample data set for Correlated Walk Analysis routine (ZIP 2K)
Crime Travel Demand tutorial (ZIP 1.3MB)
Mode Split Accessibility Function worksheet (Excel 182K)
VERSION 3.0 March 2005
UPDATE VERSION 3.1 March 2007
Update Notes (PDF 497K) New (2007-03-21)
Table of Contents, Acknowledgments and License Agreement (PDF 198K)
Chapter 1 - Introduction to CrimeStat III (PDF 116K)
Chapter 2 - Quickguide to CrimeStat III (PDF 806K)
Chapter 3 - Entering Data into CrimeStat III (PDF 1.1MB)
Chapter 4 - Spatial Distribution (PDF 2.4MB) (Updated 2005-05-13)
Chapter 5 - Distance Analysis I and II (PDF 429K)
Chapter 6 - 'Hot Spot' Analysis I (PDF 1.8MB)
Chapter 7 - 'Hot Spot' Analysis II - by Ned Levine, Richard Block, and Carolyn Rebecca Block (PDF 1.4MB)
Chapter 8 - Kernel Density Interpolation (PDF 2.7MB)
Chapter 9 - Space-Time Analysis (PDF 767K)
Chapter 10 - Journey to Crime Estimation (PDF 1.4MB) (Updated 2005-05-09)
Chapter 11 - Overview of Crime Travel Demand Modeling (PDF 686K)
Chapter 12 - Data Preparation for Crime Travel Demand Modeling (PDF 1.5MB)
Chapter 13 - Trip Generation (PDF 1.7MB)
Chapter 14 - Trip Distribution (PDF 1.4MB)
Chapter 15 - Mode Split (PDF 1.2MB)
Chapter 16 - Network Assignment (PDF 2.0MB)
Chapter 17 - Case Studies in Crime Travel Demand Modeling - by Richard Block and Dan Helms (PDF 4.7MB)
CrimeStat References (PDF 197K)
Appendix A - Dynamic Data Exchange Support - by Long Doan and Keith Alcock (PDF 58K)
Appendix B - Some Notes on the Statistical Comparison of Two Samples (PDF 111K)
Appendix C - Ordinary Least Squares and Poisson Regression Models - by Luc Anselin (PDF 286K)
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Major improvements in version 3.0 added a crime travel demand module and several new statistical routines ('Moran correlogram', 'Convex hull', 'Draw crime trips', 'Spatial-temporal moving average'), incorporated network distance along with direct and indirect distance, allowed distance to be saved as files, and improved some of the statistics from version 2.0. Version 3.1 includes a Bayesian Journey to Crime module and allows the use of weighting for the geometric and harmonic means.
Major improvements included the saving and loading of reference files, an Options section (saving and loading of Ascii parameter files, output of simulation data, coloring of tabs), additional hot spot analysis routines (mode, fuzzy mode, Risk-adjusted hierarchical clustering, STAC), and a Spatial Modeling section which included the interpolation and Journey-to-Crime routines as well as new space-time analysis routines (Knox index, Mantel index, correlated walk analysis). Two more chapters were added to the manual as well as an appendix (in total, chapters 1-10 and Appendices A-B). Additional sample data sets were added for the journey to crime routines and for the correlated walk analysis routine.
The major improvements were missing value codes, 'dat' input format, Ascii grid output, directional mean and variance in X/Y coordinates, edge corrections for the nearest neighbor and Ripley's "K" routines, expansion of the K-means clustering routine, and the addition of Journey-to-Crime calibration and estimation routines. Update notes were added to the manual and a sample data set was provided.
The initial version of CrimeStat included a Data Setup section (primary file, secondary file, reference file, measurement parameters, input in 'dbf', shape, or Ascii formats), and sections for Spatial Description (mean center, standard deviational ellipse, center of minimum distance, directional mean and variance in polar coordinates, Moran's "I", Geary's "C"), Distance Analysis (nearest neighbor index, Ripley's "K", and distance matrices), Hot Spot Analysis (nearest neighbor hierarchical spatial clustering, K-means clustering, Anselin's local Moran), and Interpolation (single and duel-kernel). Output formats included shape, BNA, and MIF. There was a program manual (chapters 1-8, Appendix A) and a "Quickguide" to the program.