Statistical analysis of spatial point patterns. 2nd ed.

*(English)*Zbl 1021.62076
London: Arnold. viii, 159 p. (2003).

Data in the form of a set of points, irregularly distributed within a region of space, is called a spatial point pattern. Examples of such data sets include location of trees in a forest, of nests in a breeding colony of birds or of nuclei in a microscopic section of tissue. The author discusses methods for the analysis of spatial patterns based on stochastic models assuming that the events (locations where the patterns were observed) are generated by some underlying random mechanism.

This is the second edition of a book by the author which appeared with the same title in 1983, see the review Zbl 0559.62088. The author says in the preface that “in the second edition I have extended the methodological discussion to cover major developments in the intervening years, but have also tried to preserve the applied flavour of the book”. He has succeded in his aim to a great extent. The contents of the book are as follows :

1. Introduction; 2. Preliminary testing; 3. Statistical methods for sparely sampled patterns; 4. Spatial point processes; 5. Models; 6. Model-fitting using summary descriptions; 7. Model-fitting using likelihood-based methods; 8. Nonparametric methods; 9. Point-process methods in spatial epidemilogy; 10. References.

The book contains major methodological themes with some technical details, with applications arising from biological sciences, especially ecology. It is well written and a welcome addition to the literature on statistical inference for spatial processes.

This is the second edition of a book by the author which appeared with the same title in 1983, see the review Zbl 0559.62088. The author says in the preface that “in the second edition I have extended the methodological discussion to cover major developments in the intervening years, but have also tried to preserve the applied flavour of the book”. He has succeded in his aim to a great extent. The contents of the book are as follows :

1. Introduction; 2. Preliminary testing; 3. Statistical methods for sparely sampled patterns; 4. Spatial point processes; 5. Models; 6. Model-fitting using summary descriptions; 7. Model-fitting using likelihood-based methods; 8. Nonparametric methods; 9. Point-process methods in spatial epidemilogy; 10. References.

The book contains major methodological themes with some technical details, with applications arising from biological sciences, especially ecology. It is well written and a welcome addition to the literature on statistical inference for spatial processes.

Reviewer: B.L.S.Prakasa Rao (New Delhi)