Spatial point patterns: methodology and applications with R
Spatial Point Patterns: Methodology and Applications with R shows scientific researchers and applied statisticians from a wide range of fields how to analyze their spatial point pattern data. Making the techniques accessible to non-mathematicians, the authors draw on their 25 years of software devel...
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| Main Authors: | , , |
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| Format: | Book |
| Language: | English |
| Published: |
Boca Raton ; London ; New York
CRC Press
[2016]
|
| Series: | Chapman & Hall/CRC interdisciplinary statistics series
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Summary: | Spatial Point Patterns: Methodology and Applications with R shows scientific researchers and applied statisticians from a wide range of fields how to analyze their spatial point pattern data. Making the techniques accessible to non-mathematicians, the authors draw on their 25 years of software development experiences, methodological research, and broad scientific collaborations to deliver a book that clearly and succinctly explains concepts and addresses real scientific questions. Practical Advice on Data Analysis and Guidance on the Validity and Applicability of Methods The first part of the book gives an introduction to R software, advice about collecting data, information about handling and manipulating data, and an accessible introduction to the basic concepts of point processes. The second part presents tools for exploratory data analysis, including non-parametric estimation of intensity, correlation, and spacing properties. The third part discusses model-fitting and statistical inference for point patterns. The final part describes point patterns with additional "structure," such as complicated marks, space-time observations, three- and higher-dimensional spaces, replicated observations, and point patterns constrained to a network of lines. |
| Item Description: | "The spatstat package ... is free, open-source software in the R language" (spatstat, a package in the R language for analysing spatial point patterns) |
| Physical Description: | xvii, 810 Seiten Illustrationen, Diagramme |
| ISBN: | 9781482210200 1482210207 |
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| 264 | 1 | |a Boca Raton ; London ; New York |b CRC Press |c [2016] | |
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Record in the Search Index
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Titel: Spatial point patterns
Autor: Baddeley, Adrian
Jahr: 2016
Contents
Preface xv
Acknowledgements xvii
I BASICS 1
1 Introduction 3
1.1 Point patterns.3
1.2 Statistical methodology for point patterns .11
1.3 About this book.16
2 Software Essentials 19
2.1 Introduction to R .19
2.2 Packages for R .34
2.3 Introduction to spat stat.36
2.4 Getting started with spat stat.39
2.5 FAQs .47
3 Collecting and Handling Point Pattern Data 49
3.1 Surveys and experiments .49
3.2 Data handling.52
3.3 Entering point pattern data into spat stat.54
3.4 Data errors and quirks.58
3.5 Windows in spatstat .61
3.6 Pixel images in spatstat .66
3.7 Line segment patterns.72
3.8 Collections of objects.73
3.9 Interactive data entry in spatstat.74
3.10 Reading GIS file formats .75
3.11 FAQs .80
4 Inspecting and Exploring Data 81
4.1 Plotting .81
4.2 Manipulating point patterns and windows .96
4.3 Exploring images.112
4.4 Using line segment patterns.119
4.5 Tessellations.120
4.6 FAQs .123
5 Point Process Methods 127
5.1 Motivation.127
5.2 Basic definitions*.128
5.3 Complete spatial randomness.132
5.4 Inhomogeneous Poisson process .137
5.5 A menagerie of models. 139
5.6 Fundamental issues. 142
5.7 Goals of analysis . 149
II EXPLORATORY DATA ANALYSIS 155
6 Intensity 157
6.1 Introduction . 157
6.2 Estimating homogeneous intensity.
6.3 Technical definition.
6.4 Quadrat counting .
6.5 Smoothing estimation of intensity function.
6.6 Investigating dependence of intensity on a covariate
6.7 Formal tests of (non-)dependence on a covariate . .
6.8 Hot spots, clusters, and local features.
6.9 Kernel smoothing of marks.
6.10 FAQs .
159
161
163
168
177
183
188
195
197
199
7 Correlation 199
7.1 Introduction.199
7.2 Manual methods.200
7.3 The K-function .203
7.4 Edge corrections for the .212
7.5 Function objects in spatstat .220
7.6 The pair correlation function .223
7.7 Standard errors and confidence intervals.230
7.8 Testing whether a pattern is completely random.233
7.9 Detecting anisotropy .236
7.10 Adjusting for inhomogeneity.242
7.11 Local indicators of spatial association .247
7.12 Third-and higher-order summary statistics.249
7.13 Theory* .250
7.14 FAQs .252
8 Spacing 255
8.1 Introduction.255
8.2 Basic methods.255
8.3 Nearest-neighbour function G and empty-space function F .261
8.4 Confidence intervals and simulation envelopes.268
8.5 Empty-space hazard.271
8.6 J-function.275
8.7 Inhomogeneous F-, G- and /-functions .277
8.8 Anisotropy and the nearest-neighbour orientation .278
8.9 Empty-space distance for a spatial pattern .279
8.10 Distance from a point pattern to another spatial pattern .282
8.11 Theory for edge corrections* .285
8.12 Palm distribution*.292
8.13 FAQs .295
Ill STATISTICAL INFERENCE 297
9 Poisson Models 299
9.1 Introduction.299
9.2 Poisson point process models.300
9.3 Fitting Poisson models in spat stat.305
9.4 Statistical inference for Poisson models .327
9.5 Alternative fitting methods .339
9.6 More flexible models .339
9.7 Theory*.341
9.8 Coarse quadrature approximation*.345
9.9 Fine pixel approximation* .351
9.10 Conditional logistic regression* .355
9.11 Approximate Bayesian inference.359
9.12 Non-loglinear models.360
9.13 Local likelihood.364
9.14 FAQs .366
10 Hypothesis Tests and Simulation Envelopes 369
10.1 Introduction.369
10.2 Concepts and terminology .369
10.3 Testing for a covariate effect in a parametric model .371
10.4 Quadrat counting tests .378
10.5 Tests based on the cumulative distribution function .381
10.6 Monte Carlo tests.384
10.7 Monte Carlo tests based on summary functions .390
10.8 Envelopes in spat stat.396
10.9 Other presentations of envelope tests.403
10.10 Dao-Genton test and envelopes.405
10.11 Power of tests based on summary functions .408
10.12 FAQs .408
11 Model Validation 411
11.1 Overview of validation techniques .411
11.2 Relative intensity .413
11.3 Residuals for Poisson processes .415
11.4 Partial residual plots .425
11.5 Added variable plots .428
11.6 Validating the independence assumption.431
11.7 Leverage and influence.436
11.8 Theory for leverage and influence*.444
11.9 FAQs .446
12 Cluster and Cox Models 449
12.1 Introduction.449
12.2 Cox processes.451
12.3 Cluster processes .459
12.4 Fitting Cox and cluster models to data .469
12.5 Locally fitted models .479
12.6 Theory*.480
12.7 FAQs .486
13 Gibbs Models 487
13.1 Introduction.487
13.2 Conditional intensity .488
13.3 Key concepts .490
13.4 Statistical insights.501
13.5 Fitting Gibbs models to data .503
13.6 Pairwise interaction models.513
13.7 Higher-order interactions.519
13.8 Hybrids of Gibbs models.527
13.9 Simulation.529
13.10 Goodness-of-fit and validation for fitted Gibbs models.535
13.11 Locally fitted models .546
13.12 Theory: Gibbs processes*.547
13.13 Theory: Fitting Gibbs models*.553
13.14 Determinantal point processes .558
13.15 FAQs .559
14 Patterns of Several Types of Points 561
14.1 Introduction.561
14.2 Methodological issues .561
14.3 Handling multitype point pattern data .567
14.4 Exploratory analysis of intensity .574
14.5 Multitype Poisson models.583
14.6 Correlation and spacing.591
14.7 Tests of randomness and independence.605
14.8 Multitype Gibbs models .611
14.9 Hierarchical interactions .620
14.10 Multitype Cox and cluster processes.625
14.11 Other multitype processes.628
14.12 Theory* .629
14.13 FAQs .631
IV ADDITIONAL STRUCTURE 635
15 Higher-Dimensional Spaces and Marks 637
15.1 Introduction.637
15.2 Point patterns with numerical or multidimensional marks.638
15.3 Three-dimensional point patterns.650
15.4 Point patterns with any kinds of marks and coordinates .657
15.5 FAQs .659
16 Replicated Point Patterns and Designed Experiments 661
16.1 Introduction.661
16.2 Methodology .662
16.3 Lists of objects .663
16.4 Hyperframes .666
16.5 Computing with hyperframes.671
16.6 Replicated point pattern datasets in spatstat.673
16.7 Exploratory data analysis.678
16.8 Analysing summary functions from replicated patterns .680
16.9 Poisson models .
16.10 Gibbs models .698
16.11 Model validation .702
16.12 Theory*.706
16.13 FAQs .708
17 Point Patterns on a Linear Network 709
17.1 Introduction.709
17.2 Network geometry .711
17.3 Data handling.712
17.4 Intensity.719
17.5 Poisson models .725
17.6 Intensity on a tree.729
17.7 Pair correlation function .732
17.8 AT-function.735
17.9 FAQs .743
Index of Notation 745
Bibliography 751
Index 791 |
| any_adam_object | 1 |
| author | Baddeley, Adrian 1955- Rubak, Ege Turner, Rolf |
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| discipline | Geowissenschaften Informatik Mathematik |
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| id | DE-604.BV043424760 |
| illustrated | Illustrated |
| indexdate | 2025-03-27T15:00:44Z |
| institution | BVB |
| isbn | 9781482210200 1482210207 |
| language | English |
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| record_format | marc |
| series2 | Chapman & Hall/CRC interdisciplinary statistics series |
| spelling | Baddeley, Adrian 1955- Verfasser (DE-588)1068493526 aut Spatial point patterns methodology and applications with R Adrian Baddeley (Curtin University, Australia), Ege Rubak (Aalborg University, Denmark), Rolf Turner (University of Auckland, New Zealand) Boca Raton ; London ; New York CRC Press [2016] © 2016 xvii, 810 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Chapman & Hall/CRC interdisciplinary statistics series "The spatstat package ... is free, open-source software in the R language" (spatstat, a package in the R language for analysing spatial point patterns) Spatial Point Patterns: Methodology and Applications with R shows scientific researchers and applied statisticians from a wide range of fields how to analyze their spatial point pattern data. Making the techniques accessible to non-mathematicians, the authors draw on their 25 years of software development experiences, methodological research, and broad scientific collaborations to deliver a book that clearly and succinctly explains concepts and addresses real scientific questions. Practical Advice on Data Analysis and Guidance on the Validity and Applicability of Methods The first part of the book gives an introduction to R software, advice about collecting data, information about handling and manipulating data, and an accessible introduction to the basic concepts of point processes. The second part presents tools for exploratory data analysis, including non-parametric estimation of intensity, correlation, and spacing properties. The third part discusses model-fitting and statistical inference for point patterns. The final part describes point patterns with additional "structure," such as complicated marks, space-time observations, three- and higher-dimensional spaces, replicated observations, and point patterns constrained to a network of lines. R Programm (DE-588)4705956-4 gnd rswk-swf Datenanalyse (DE-588)4123037-1 gnd rswk-swf Modellierung (DE-588)4170297-9 gnd rswk-swf Räumliche Statistik (DE-588)4386767-4 gnd rswk-swf Räumliche Statistik (DE-588)4386767-4 s Datenanalyse (DE-588)4123037-1 s Modellierung (DE-588)4170297-9 s R Programm (DE-588)4705956-4 s DE-604 Rubak, Ege Verfasser (DE-588)1118759486 aut Turner, Rolf Verfasser (DE-588)1118759702 aut Erscheint auch als Online-Ausgabe, PDF 978-1-4822-1021-7 (DE-604)BV048256621 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028842647&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Baddeley, Adrian 1955- Rubak, Ege Turner, Rolf Spatial point patterns methodology and applications with R R Programm (DE-588)4705956-4 gnd Datenanalyse (DE-588)4123037-1 gnd Modellierung (DE-588)4170297-9 gnd Räumliche Statistik (DE-588)4386767-4 gnd |
| subject_GND | (DE-588)4705956-4 (DE-588)4123037-1 (DE-588)4170297-9 (DE-588)4386767-4 |
| title | Spatial point patterns methodology and applications with R |
| title_auth | Spatial point patterns methodology and applications with R |
| title_exact_search | Spatial point patterns methodology and applications with R |
| title_full | Spatial point patterns methodology and applications with R Adrian Baddeley (Curtin University, Australia), Ege Rubak (Aalborg University, Denmark), Rolf Turner (University of Auckland, New Zealand) |
| title_fullStr | Spatial point patterns methodology and applications with R Adrian Baddeley (Curtin University, Australia), Ege Rubak (Aalborg University, Denmark), Rolf Turner (University of Auckland, New Zealand) |
| title_full_unstemmed | Spatial point patterns methodology and applications with R Adrian Baddeley (Curtin University, Australia), Ege Rubak (Aalborg University, Denmark), Rolf Turner (University of Auckland, New Zealand) |
| title_short | Spatial point patterns |
| title_sort | spatial point patterns methodology and applications with r |
| title_sub | methodology and applications with R |
| topic | R Programm (DE-588)4705956-4 gnd Datenanalyse (DE-588)4123037-1 gnd Modellierung (DE-588)4170297-9 gnd Räumliche Statistik (DE-588)4386767-4 gnd |
| topic_facet | R Programm Datenanalyse Modellierung Räumliche Statistik |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028842647&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT baddeleyadrian spatialpointpatternsmethodologyandapplicationswithr AT rubakege spatialpointpatternsmethodologyandapplicationswithr AT turnerrolf spatialpointpatternsmethodologyandapplicationswithr |