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Statistical Analysis of Geographical Data
Language: en
Pages: 264
Authors: Simon James Dadson
Categories: Science
Type: BOOK - Published: 2017-05-08 - Publisher: John Wiley & Sons

9.5 Assumptions and caveats with regression -- 9.6 Is the regression significant? -- 9.7 Coefficient of determination -- 9.8 Confidence intervals and hypothesis tests concerning regression parameters -- 9.9 Reduced major axis regression -- 9.10 Summary -- Exercises -- 10 Spatial Statistics -- 10.1 Spatial Data -- 10.2 Summarizing Spatial
Spatial Structure and Spatial Interaction
Language: en
Pages: 36
Authors: R. J. Bennett
Categories: Science
Type: BOOK - Published: 1985 - Publisher:

Books about Spatial Structure and Spatial Interaction
A Casebook for Spatial Statistical Data Analysis
Language: en
Pages: 506
Authors: Daniel A. Griffith, Larry J. Layne, J. K. Ord, Akio Sone
Categories: Mathematics
Type: BOOK - Published: 1999 - Publisher: Oxford University Press on Demand

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
Statistics for Spatial Data
Language: en
Pages: 928
Authors: Noel Cressie
Categories: Mathematics
Type: BOOK - Published: 2015-03-18 - Publisher: John Wiley & Sons

The Wiley Classics Library consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians,
The SAGE Handbook of Spatial Analysis
Language: en
Pages: 528
Authors: A Stewart Fotheringham, Peter A Rogerson
Categories: Social Science
Type: BOOK - Published: 2008-12-22 - Publisher: SAGE

The widespread use of Geographical Information Systems (GIS) has significantly increased the demand for knowledge about spatial analytical techniques across a range of disciplines. As growing numbers of researchers realise they are dealing with spatial data, the demand for specialised statistical and mathematical methods designed to deal with spatial data