Applied Statistics

12Spatial Statistics

12.1 Introduction

Spatial statistics is a part of applied statistics and is concerned with modelling and analysis of spatial data. By spatial data we mean data where, in addition to the (primary) phenomenon of interest, the relative spatial locations of observations are also recorded because these may be important for the interpretation of data. This is of primary importance in earth‐related sciences such as geography, geology, hydrology, ecology, and environmental sciences, but also in other scientific disciplines concerned with spatial variations and patterns such as astrophysics, economics, agriculture, forestry, and epidemiology, and, at a microscopic scale, medical and health research. Spatial statistics uses nearly all methods described in the first eleven chapters of this book and also multivariate analysis and Bayesian methods, neither of which are discussed in this book. We therefore restrict ourselves in this chapter to a few basic principles and give hints for further reading for other important methods. As a consequence of this, the list of references is relatively long.

We restrict our attention to continuous characteristics and to Gaussian distributions and analyse examples with the program package R as we did in other chapters of this book. Those who prefer SAS and understand a bit of German are referred to the procedures in 6/61 of Rasch et al. (2008).

• 6/61/0000 Spatial Statistics – Introduction
• 6/61/1010 Estimation of the covariance function ...