List of Data Sets Analyzed                 xv
  Abbreviations                                      xvi
  PART I: THEORETICAL BACKGROUND
    Introduction                                     3  
      Parallels between Spatial Autoregression       6  
      and Geostatistics
      The Many Faces of Spatial Autocorrelation      9  
      The Moran Coefficient Scatterplot Tool         15 
      Multivariate Spatial Association               18 
      Heterogeneity and Locational Information       25 
      The Semivariogram Plot Tool                    34 
      Computer Code for Implementing Spatial         39 
      Statistical Analyses
        SAS Code for Computing MC Using Standard     62 
        Regression Techniques.
        Directions for Using ArcInfo to Construct    64 
        a Thiessen Polygon Surface Partitioning
        for a Set of Georeferenced Points.
        SAS Macros Used for Converting among         67 
        Degrees, Decimal Degrees and Radians
    Important Modeling Assumptions                   69 
      The Relative Importance of the Principal       71 
      Assumptions
      Variable Transformations                       73 
      Transforming in Search of Normality            75 
      Transforming in Search of Constant Variance    79 
      Linearity: Exploitation of Linear              83 
      Relationships by Linear Statistical Models
      An Absence of Independence: The Presence of    86 
      Spatial Autocorrelation in Georeferenced
      Data
      Exploring Residuals in Spatial Analysis        105
      Other Statistical Frequency Distribution       111
      Assumptions
    Popular Spatial Autoregressive and               120
    Geostatistical Models
      Spatial Autoregressive Models                  121
      Geostatistical Models                          133
      Articulating Relationships Between Spatial     142
      Autoregressive and Geostatistical Models
      Computer Code for Spatial Autoregressive       153
      and Semivariogram Modeling
        SAS Code for Estimating Equations            165
        (3.7a-c)---the CAR Model
        SPSS Code for Estimating Equations           169
        (3.7a-c)---the CAR Model
        SAS Code for Estimating Equations (3.8) &    172
        (3.9)---the SAR & AR Models
        SPSS Code for Estimating Equations (3.8)     175
        & (3.9)---the SAR & AR Models
        SAS Code for Selected Semivariogram Models   178
        SPSS Code for Selected Semivariogram         194
        Models
  PART II: GEOREFERENCED DATA SET CASE STUDIES       205
    Analysis of Georeferenced Socioeconomic          207
    Attribute Variables
      The Cliff-Ord Eire Population Data             211
      Urban Population Density                       214
      Residential Insurance Coverage in Chicago      218
      Urban Crime in Columbus, Ohio                  222
      Geographic Distribution of Minorities          227
      across Syracuse, New York
      Concluding Comments: Spatial                   232
      Autocorrelation and Socioeconomic Attribute
      Variables
        Centroids Derived from a Digitized           234
        Version of Cliff and Ord's Map of Eire
        (1981, 207) Using ArcInfo
    Analysis of Georeferenced Natural Resources      235
    Attribute Variables
      Kansas Oil Wells Data                          241
      Natural Resources Inventory Data               245
      Island Biogeography: Plant Species Data        265
      Weather Station Rainfall Data                  272
      Drainage Basin Runoff Data                     277
      Digital Elevation Data                         284
      Preclassified Remotely Sensed Image            292
      Reflectance Data
      Concluding Comments: Spatial                   302
      Autocorrelation and Natural Resources
      Attribute Variables
    Analysis of Georeferenced Agricultural Yield     305
    Variables
      The Mercer-Hall Straw Yield Data               311
      The Wiebe Wheat Yield Data                     316
      The Broadbalk Wheat and Straw Yield Data       320
      Sugar Cane Production in Puerto Rico           330
      Milk Production in Puerto Rico                 337
      Concluding Comments: Spatial                   350
      Autocorrelation and Agricultural Yield
      Variables
    Analysis of Georeferenced Pollution Variables    353
      Southwestern Pennsylvania Coal Ash             360
      EMAP Indicators of Ecological Condition        365
      Great Smoky Mountains Water pH                 373
      Chemical Elements in Northwest Texas           378
      Groundwater
      Hazardous Waste Contamination of Soil:         390
      Dioxin
      Concluding Comments: Spatial                   393
      Autocorrelation and Pollution Variables
    Analysis of Georeferenced Epidemiological        396
    Variables
      Glasgow Standardized Mortality Rates           405
      Pediatric Lead Poisoning in Syracuse, New      410
      York
      Fox Rabies in Germany                          417
      Concluding Comments: Spatial                   423
      Autocorrelation and Epidemiological
      Variables
  PART III: VISUALIZING WHAT IS NOT OBSERVED         427
    Exploding Georeferenced Data When Maps Have      428
    Holes or Gaps: Estimating Missing Data Values
    and Kriging
      An Introduction to EM Estimation               430
      Estimating Missing Values: Two Simplified      432
      Georeferenced Data Illustrations
      Estimating a Conspicuous Missing Data Value    438
      for the Coal-Ash Data Set
      Estimating Conspicuous Missing Data Values     441
      for an Agricultural Experiment
      Estimating Missing Median Family Income        445
      Data for Ottawa-Hull
      Generalizing a Map Surface with Kriging        447
      A Cross-Validation Example                     451
      Concluding Comments: Exploding                 454
      Georeferenced Data
    Concluding Comments                              457
      More about the Nature of Georeferenced Data    459
      Reflections on Spatial Data Model              460
      Specifications
      Implications regarding Relations between       469
      Spatial Autoregressive and Geostatistical
      Models
      Reflections on Kriging                         473
      Spatial Statistics and GIS                     475
      Now Is the Time for All Good Spatial           476
      Scientists to
      Some Questions Yet Unanswered: Future          479
      Research
  Epilogue                                           484
  References                                         488
  Subject Index                                      503