The first comprehensive, object-oriented package for the analysis of spatial data. Providing a whole new set of analysis tools, S+SPATIALSTATS was created specifically for the exploration and modelling of spatially correlated data, and, as such, can be used to analyse data in such areas as environmental, mining, and petroleum engineering, natural resources, geography, epidemiology, demography, and others where data is sampled spatially.
S+SpatialStats: User's Manual for Windows and UNIX
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Editorial Reviews
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From a review: SHORT BOOK REVIEWS "The book is well laid out, similar in style to a number of LaTex manuals, which I find aesthetically pleasing and easy to navigate. A concise introduction gives a good overview of the three types of spatial data and some associated spatial statistical concepts. ... I highly recommend this book."
From the Publisher
S-PLUS has become the most popular statistical software program for statistical researchers in many disciplines. This manual provides the documentation for their spatial statistics module, a program of interest to researchers in statistics, petroleum engineering, natural resources, geography, geology, epidemiology, and demography.
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Inside This Book
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First Sentence:
Spatial data consist of measurements or observations taken at specific locations or within specific regions. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
scallops data, analyzing geostatistical data, coal ash data, loess model, point pattern object, kriging prediction standard errors, spatial linear model, rainfall coverage, neighbor matrices, neighbor matrix, hexagonal binning, hexagon mosaic maps, point pattern data, covariance family, empirical variogram, sids data, maple data, spatial correlation measure, empirical correlogram, hexagonal bins, logical flag, median polishing, argument neighbor, neighbor weights, interpolated distances Key Phrases - Capitalized Phrases (CAPs): (learn more)
Lansing Woods, Visualizing Spatial Data, Analyzing Spatial Point Patterns, Median Mean, Analyzing Lattice Data, Jan Feb Mar, Measures of Spatial Randomness, Oct Nov Dec, Spatial Correlation Estimate Statistic, Gentle Introduction, Crash Course, Likelihood Ratio Test Chisquare, Organizing Your Working Data, Value Std, Variance-Covariance Matrix of Coefficients New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Spatial data consist of measurements or observations taken at specific locations or within specific regions. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
scallops data, analyzing geostatistical data, coal ash data, loess model, point pattern object, kriging prediction standard errors, spatial linear model, rainfall coverage, neighbor matrices, neighbor matrix, hexagonal binning, hexagon mosaic maps, point pattern data, covariance family, empirical variogram, sids data, maple data, spatial correlation measure, empirical correlogram, hexagonal bins, logical flag, median polishing, argument neighbor, neighbor weights, interpolated distances Key Phrases - Capitalized Phrases (CAPs): (learn more)
Lansing Woods, Visualizing Spatial Data, Analyzing Spatial Point Patterns, Median Mean, Analyzing Lattice Data, Jan Feb Mar, Measures of Spatial Randomness, Oct Nov Dec, Spatial Correlation Estimate Statistic, Gentle Introduction, Crash Course, Likelihood Ratio Test Chisquare, Organizing Your Working Data, Value Std, Variance-Covariance Matrix of Coefficients 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 14
books:
See all 14 books this book cites
- Statistics for Spatial Data (Wiley Series in Probability and Statistics) by Noel Cressie on 10 pages
- Spatial Data Analysis in the Social and Environmental Sciences by Robert Haining on 7 pages
- Spatial Statistics (Wiley Series in Probability and Statistics) by Brian D. Ripley on 6 pages
- Statistical Analysis of Spatial Point Patterns by Peter J. Diggle on 6 pages
- Mining Geostatistics by A.G. Journel on 4 pages
See all 14 books this book cites
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