Summary
Contents
Subject index
This is a proposal for a core text in geocomputation; the use of computational techniques to model and solve problems – population, environment, planning, etc etc - in spatial context. It's multi-disciplinary and inter-disciplinary so this text is a generic primer that looks at: visualisation and exploratory spatial data analysis; space time modeling; spatial algorithms; spatial regression and statistics; and decision making. The edited text is organized in five sections: 1. Introducing Applied Geocomputation; 2. Describing how the world looks; 3. Exploring movements in space; 4. Making geographical decisions; and 5. Explaining how the world works
Circular Statistics
Circular Statistics
Introduction
Geocomputation involves the analysis of data in many forms, including real numbers that might include information on distances or times, counts derived from census tables, or categorical variables drawn from survey data, to name only a select few. The analysis of these datasets requires the use of statistical methods based upon distributions with appropriate support, for example the normal distribution which has support over the real numbers (i.e. negative or positive values) and the Poisson distribution which has support over the natural numbers (i.e. count data, see Nakaya, Chapter 12). In this chapter we consider another type of data of interest to geographers: namely, angular or directional data.
Angular quantities are real numbers ...
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