Daniel A. Griffith, Ashbel Smith Professor of Geography and Geospatial Information Science, School of Economic, Political, and Policy Sciences, University of Texas at Dallas and Bin Li, Professor of Geography, Department of Geography and Environmental Studies, Central Michigan University, US

‘With widespread and increasingly available georeferenced data, this book offers a timely assessment of contemporary methods, models, and metrics—such as the eigenvector spatial filtering approach to handling spatial autocorrelation—in spatial statistics. I salute the authors for this enlightening contribution! The book will greatly empower us to better uncover mechanisms behind georeferenced data.’

• Contents: Preface 1. An advanced introduction to spatial statistics: motivation and scope 2. Describing spatial random variables 3. Spatial statistical model parameter estimation 4. A spatial statistical modeling workflow 5. Applications from A to Z of spatial statistical modeling 6. Nonparametric spatial statistical models Afterword References Index

Daniel A. Griffith, Ashbel Smith Professor of Geography and Geospatial Information Science, School of Economic, Political, and Policy Sciences, University of Texas at Dallas and Bin Li, Professor of Geography, Department of Geography and Environmental Studies, Central Michigan University, US

‘With widespread and increasingly available georeferenced data, this book offers a timely assessment of contemporary methods, models, and metrics—such as the eigenvector spatial filtering approach to handling spatial autocorrelation—in spatial statistics. I salute the authors for this enlightening contribution! The book will greatly empower us to better uncover mechanisms behind georeferenced data.’

• Contents: Preface 1. An advanced introduction to spatial statistics: motivation and scope 2. Describing spatial random variables 3. Spatial statistical model parameter estimation 4. A spatial statistical modeling workflow 5. Applications from A to Z of spatial statistical modeling 6. Nonparametric spatial statistical models Afterword References Index

Daniel A. Griffith, Ashbel Smith Professor of Geography and Geospatial Information Science, School of Economic, Political, and Policy Sciences, University of Texas at Dallas and Bin Li, Professor of Geography, Department of Geography and Environmental Studies, Central Michigan University, US

‘With widespread and increasingly available georeferenced data, this book offers a timely assessment of contemporary methods, models, and metrics—such as the eigenvector spatial filtering approach to handling spatial autocorrelation—in spatial statistics. I salute the authors for this enlightening contribution! The book will greatly empower us to better uncover mechanisms behind georeferenced data.’

• Contents: Preface 1. An advanced introduction to spatial statistics: motivation and scope 2. Describing spatial random variables 3. Spatial statistical model parameter estimation 4. A spatial statistical modeling workflow 5. Applications from A to Z of spatial statistical modeling 6. Nonparametric spatial statistical models Afterword References Index