NCGIA
National Center for Geographic Information and Analysis
Spatial Data Analysis and GIS:
Interfacing GIS and Econometric Software
By
Luc Anselin, Sheri Hudak and Rustin Dodson University of California, Santa Barbara
Technical Report 93-7 May 1993
Simonett Center for Spatial Analysis State University of New York University of Maine University of California 301 Wilkeson Quad, Box 610023 348 Boardman Hall 35 10 Phelps Hall Buffalo NY 14261-0001 Orono ME 04469-5711 Santa Barbara, CA 93106-4060 Office (716) 645-2545 Office (207) 581-2149 Office (805) 893-8224 Fax (716) 645-5957 Fax (207) 581-2206 Fax (805) 893-8617 [email protected] [email protected] [email protected] TABLE OF CONTENTS
CHAPTER 1: INTRODUCTION BACKGROUND AND MOTIVATION ORGANIZATION OF THE REPORT ECONOMETRIC SOFTWARE Versions Hardware Problem Size Limitations Executing the Routines Gauss Limdep Rats Shazam Splus REFERENCES
CHAPTER 2: EXTRACTING SPATIAL WEIGHTS MATRICES FROM A GIS INTRODUCTION OVERVIEW OF THE ROUTINES General Characteristics C Language Programs Arc/Info AML Macros REFERENCES RASCONT.C - contiguity-based spatial weights matrices from raster polygons RASDIST.C - distance-based spatial weights matrices from raster polygons CONWEIGHT.AML - contiguity-based W-matrices from Arc/Info DISWEIGHT.AML - distance-based W-matrices from Arc/Info SP2FULL.C - converts sparse matrices to full format
CHAPTER 3: PRE-PROCESSING AND MANIPULATING SPATIAL WEIGHTS MATRICES INTRODUCTION OVERVIEW OF THE ROUTINES REFERENCES THE WRSTD.* AND EIGENW.* PROGRAMS Table 3.1 - Gauss: WRSTD.GAS Table 3.2 – Gauss: EIGENW.GAS Table 3.3 - Limdep: WRSTD.LIM Table 3.4 - Rats: WRSTD.RAT Table 3.5 – Shazam: WRSTD.SHA Table 3.6 - Splus: WRSTD.SPL Table 3.7 - Splus: EIGENW.SPL
CHAPTER 4: REGRESSION DIAGNOSTICS INTRODUCTION METHODOLOGICAL BACKGROUND OVERVIEW OF THE ROUTINES REFERENCES THE REGDIAG.* PROGRAMS: REGRESSION DIAGNOSTICS Table 4.1 – Gauss: REGDIAG.GAS Table 4.2 – Limdcp: REGDIAG.LIM Table 4.3 - Rats: REGDIAG.RAT Table 4.4 – Shazam: REGDIAG.SHA Table 4.5 - Splus: REGDIAG.SPL
CHAPTER 5: MAXIMUM LIKELIHOOD ESTIMATION OF SPATIAL AUTOREGRESSIVE MODELS INTRODUCTION METHODOLOGICAL BACKGROUND OVERVIEW OF THE ROUTINES REFERENCES THE MLYX.* PROGRAMS: SPATIAL LAG MODEL Table 5.1 - Gauss: MLYX.GAS Table 5.2 - Limdep: MLYX.LIM Table 5.3 - Rats: MLYX.RAT Table 5.4 - Shazam: MLYX.SHA Table 5.5 - Splus: MLYX.SPL
CHAPTER 6: MAXIMUM LIKELIHOOD ESTIMATION OF MODELS W! SPATIAL AUTOREGRESSIVE ERRORS INTRODUCTION METHODOLOGICAL BACKGROUND OVERVIEW OF THE ROUTINES REFERENCES THE MLER.* PROGRAMS: SPATIAL ERROR MODEL Table 6.1 - Gauss: MLER.GAS Table 6.2 - Limdep: MLER.LIM Table 6.3 - Rats: MLER.RAT Table 6.4 – Shazam: MLER.SHA Table 6.5 - Splus: MLER.SPL
APPENDICES APPENDIX 1: CONTENTS OF THE INCLUDED DISKETTE GIS: The GIS W-matrix extraction programs ROUTINES: The statistical routines COLUMBUS: The Columbus, Ohio dataset APPENDIX 2: OVERVIEW OF STEPS FOR USING THIS REPORT APPENDIX 3: SPARSE MATRIX FILE FORMATS Sparse Binary Format Sparse General Format APPENDIX 4: SOURCE CODE FOR CHAPTER 2 ROUTINES RASCONT.C RASDIST.C SP2FULL.C INF2SMF.C CONWEIGHT.AML DISWEIGHT.AML APPENDIX 5: MAP OF COLUMBUS, OHIO NEIGHBORHOODS