本教材是 spatstat程序包的作者 A Baddeley教授介绍用R做点格局分析的讲义, 也是后来 Spatial Point Patterns: Methodology and Applications with R 一书的基础。由于该书出版不久, 仍然下载不到pdf。但是书中的绝大多数内容, 在本讲义中都已经包括了, 所以还是非常值得一读的。 内容参见附录。
Contents
PART I. OVERVIEW 5
1 Introduction 6
2 Statistical formulation 13
3 The R system 18
4 Introduction to spatstat 20
PART II. DATA TYPES & DATA ENTRY 31
5 Objects, classes and methods in R 32
6 Entering point pattern data into spatstat 38
7 Converting from GIS formats 45
8 Windows in spatstat 46
9 Manipulating point patterns 53
10 Pixel images in spatstat 63
11 Tessellations 71
PART III. INTENSITY 77
12 Exploring intensity 78
13 Dependence of intensity on a covariate 82
PART IV. POISSON MODELS 87
14 Tests of Complete Spatial Randomness 88
15 Maximum likelihood for Poisson processes 95
16 Checking a fitted Poisson model 106
17 Spatial logistic regression 112
PART V. INTERACTION 113
18 Exploring dependence between points 114
19 Distance methods for point patterns 115
20 Simulation envelopes and goodness-of-fit tests 132
21 Spatial bootstrap methods 139
22 Simple models of non-Poisson patterns 139
23 Model-fitting using summary statistics 144
24 Exploring local features 148
25 Adjusting for inhomogeneity 149
PART VI. GIBBS MODELS 155
26 Gibbs models 156
27 Fitting Gibbs models 162
28 Validation of fitted Gibbs models 171
PART VII. MARKED POINT PATTERNS 177
29 Marked point patterns 178
30 Handling marked point pattern data 181
31 Exploratory tools for multitype point patterns 187
32 Exploratory tools for marked point patterns 200
33 Multitype Poisson models 204
34 Gibbs models for multitype point patterns 210
PART VIII. HIGHER DIMENSIONS AND OTHER SPATIAL DATA 215
35 Line segment data 216
36 Point patterns in 3D 218
37 Point patterns in multi-dimensional space-time 219
38 Replicated data and hyperframes 221
39 Stochastic geometry 222
40 Further information on spatstat 224
Bibliography 225
Index 228