This Advanced Introduction provides a critical review and discussion of research concerning spatial statistics, differentiating between it and spatial econometrics, to answer a set of core questions covering the geographic-tagging-of-data origins of the concept and its theoretical underpinnings, conceptual advances, and challenges for future scholarly work. It offers a vital tool for understanding spatial statistics and surveys how concerns about violating the independent observations assumption of statistical analysis developed into this discipline.
This work has been undertaken by geographers, statisticians, regional scientists, econometricians, and others (e. g. , sociologists).
The book is suitable for postgraduate and advanced undergraduate students in mathematics and statistics.
It is accompanied by a suite of data and R code on Github to help readers practise techniques via replication and exercises. This text will be a valuable resource for advanced students of econometrics, spatial planning and regional science.
The theoretical upper bound is 2 l/Z N Z Z wij(Yi — 7) Ills N if' "=1 N N 221147 ZZ i;éjj=1 i=1 (cf. Cliff and Ord 1981, p. 21; Haining 1990, p. 234; Bailey and Gatrell 1995, p. 270). Moran's I is very similar to Pearson's ...
Assembling a collection of very prominent researchers in the field, the Handbook of Spatial Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects of this maturing area.
This is a definitive ′how to′ that takes students - of any discipline - from coding to actual applications and uses of R.
Difficult concepts are well explained and supported by excellent examples in R code, allowing readers to see how each of the methods is implemented in practice" - Professor Tao Cheng, University College London Focusing specifically on ...
Lee, L.-F. (2004). “Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Econometric Models,” Econometrica, 72, 1899-1926. Lee, M. and R.K. Pace (2005). “Spatial Distribution of Retail Sales,” Journal of Real ...
Data in the Wild is a series of practical books, sharing key tools and methods for the collection, analysis and interpretation of environmental data. They are published rapidly in print and digital formats.
This work has been undertaken by geographers, statisticians, regional scientists, econometricians, and others (e. g., sociologists).