Spatial Data Analysis by Example: Categorical and directional data
Volume 1 describes recent advances in analytical methods of point pattern data and surveys regression methods for analysis of quantitative spatial data. Volume 2 confronts the problems presented by categorical and directional data, including measurements taken in situ, and the study of the movements of people and animals. Emphasis is on application of the techniques, which are illustrated through numerous examples, tables and figures. Heavily referenced.
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CONTINGENCY TABLES FROM MAPS
MORE SPECIALISED TECHNIQUES FOR CONTINGENCY
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AB/AC/BC alternative analysis angle appropriate approximate autocorrelation Biometrika black-headed gull butterfly calculate cell centred Chapter chi-squared chi-squared distribution circular data confidence interval consider constraints contingency table correlation corresponding critical values data of Table data sets degrees of freedom destination distance eigenvalues eigenvectors equation Example expected frequencies Fingleton function GENSTAT given in Table gravity model groups independence model individual interaction Kent distribution Langevin distribution linear locations log-linear models Mardia marginal matrix maximum likelihood estimate mean direction measure methods migration Mises distribution model fitted normal distribution null hypothesis observed frequencies obtain origin parameter estimates percentage points population possible probability procedure quadrats quasi-symmetry random ratio refer region ringlet rotation sample saturated model sea star Significance level simple spatial data species speckled wood suggested summary test statistic uniform association model uniform distribution unit normal distribution Upton variable variance vector xl distribution Y2 values zero