This volume compiles geostatistical and spatial autoregressive data analyses involving georeferenced socioeconomic, natural resources, agricultural, pollution, and epidemiological variables. Benchmark analyses are followed by analyses of readily available data sets, emphasizing parallels between geostatistical and spatial autoregressive findings. Both SAS and SPSS code are presented for implementation purposes. This informative casebook will serve geographers, regional scientists, applied spatial statisticians, and spatial scientists from across disciplines.
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Daniel A. Griffith is at Syracuse University.
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Inside This Book
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First Sentence:
In the Introduction to Practical Handbook of Spatial Statistics (Arlinghaus 1996a, 1-15), Griffith stresses that spatial statistics is a crucial, rapidly growing, emerging area of statistics, rife with fascinating theoritical and applied research opportunities. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
spatial autocorrelation latent, semivariogram plot, exponential semivariogram model, latent spatial autocorrelation, mean response specification, wolfcamp aquifer data, agricultural productivity variables, spatial autoregressive specification, few distance classes, plant species counts, autoregressive analyses, geographic connectivity matrix, power semivariogram model, spatial dependency field, georeferenced data points, low outlier values, positive spatial dependency, weak positive spatial autocorrelation, fox rabies cases, detected spatial autocorrelation, maximum distance class, semivariance values, autoregressive model specification, outlier accounting, spatial dependency effects Key Phrases - Capitalized Phrases (CAPs): (learn more)
Puerto Rico, Puerto Rican, Chesapeake Bay, High Peak, Long Island Coast, Delaware Bay, Monte Carlo, Galapagos Islands, New York, Geary Ratio, North Carolina, Wayne County, Onondaga County, San Juan Arecibo Mayaguez Ponce Caguas, Rio Piedras, Census Bureau, Great Smoky Mountains, Handbook of Small Data Sets, United States, Cressie's Wolfcamp, Great South, Hamilton's New England, Las Marias, Love Canal, Santa Isabel New!
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
In the Introduction to Practical Handbook of Spatial Statistics (Arlinghaus 1996a, 1-15), Griffith stresses that spatial statistics is a crucial, rapidly growing, emerging area of statistics, rife with fascinating theoritical and applied research opportunities. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
spatial autocorrelation latent, semivariogram plot, exponential semivariogram model, latent spatial autocorrelation, mean response specification, wolfcamp aquifer data, agricultural productivity variables, spatial autoregressive specification, few distance classes, plant species counts, autoregressive analyses, geographic connectivity matrix, power semivariogram model, spatial dependency field, georeferenced data points, low outlier values, positive spatial dependency, weak positive spatial autocorrelation, fox rabies cases, detected spatial autocorrelation, maximum distance class, semivariance values, autoregressive model specification, outlier accounting, spatial dependency effects Key Phrases - Capitalized Phrases (CAPs): (learn more)
Puerto Rico, Puerto Rican, Chesapeake Bay, High Peak, Long Island Coast, Delaware Bay, Monte Carlo, Galapagos Islands, New York, Geary Ratio, North Carolina, Wayne County, Onondaga County, San Juan Arecibo Mayaguez Ponce Caguas, Rio Piedras, Census Bureau, Great Smoky Mountains, Handbook of Small Data Sets, United States, Cressie's Wolfcamp, Great South, Hamilton's New England, Las Marias, Love Canal, Santa Isabel New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 73
books:
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- A Handbook of Small Data Sets (Chapman & Hall Statistics Text) by David J. Hand on 8 pages
- Practical Handbook of Spatial Statistics by Sandra Arlinghaus on 4 pages
- Spatial Statistics: Past, Present, and Future (Institute of Mathematical Geography, Monograph Ser, No 12) by Daniel A. Griffith on 4 pages
- Statistics for Spatial Data (Wiley Series in Probability and Statistics) by Noel Cressie in Front Matter, and Back Matter
- Spatial Data Analysis in the Social and Environmental Sciences by Robert Haining in Front Matter, and Back Matter
See all 73 books this book cites
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