Applied spatial data analysis with R:
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| Main Authors: | , , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
New York, NY
Springer
2008
|
| Series: | Use R!
|
| Subjects: | |
| Online Access: | Inhaltstext Inhaltsverzeichnis |
| Physical Description: | XIV, 374 S. Ill., graph. Darst., Kt. 235 mm x 155 mm |
| ISBN: | 9780387781709 9780387781716 |
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| 100 | 1 | |a Bivand, Roger |d 1951- |e Verfasser |0 (DE-588)109813561 |4 aut | |
| 245 | 1 | 0 | |a Applied spatial data analysis with R |c Roger S. Bivand ; Edzer J. Pebesma ; Virgilio Gómez-Rubio |
| 264 | 1 | |a New York, NY |b Springer |c 2008 | |
| 300 | |a XIV, 374 S. |b Ill., graph. Darst., Kt. |c 235 mm x 155 mm | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Use R! | |
| 650 | 4 | |a Datenverarbeitung | |
| 650 | 4 | |a R (Computer program language) | |
| 650 | 4 | |a Spatial analysis (Statistics) |x Data processing | |
| 650 | 0 | 7 | |a R |g Programm |0 (DE-588)4705956-4 |2 gnd |9 rswk-swf |
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Record in the Search Index
| _version_ | 1805090873535365120 |
|---|---|
| adam_text |
Contents
Preface
.
VII
1
Hello World:
Introducing Spatial Data
. 1
1.1
Applied
Spatial Data Analysis
. 1
1.2
Why Do We
Use
R
. 2
1.2.1 .
In General?
. 2
1.2.2 .
for Spatial Data Analysis?
.
З
1.3
R
and GIS
. 4
1.3.1
What is
GIS?
. 4
1.3.2
Service-Oriented Architectures
. 6
1.3.3
Further Reading on
GIS
. 6
1.4
Types of Spatial Data
. 7
1.5
Storage and Display
. 10
1.6
Applied Spatial Data Analysis
. 11
1.7
R
Spatial Resources
. 13
1.7.1
Online Resources
. 14
1.7.2
Layout of the Book
. 14
Part I Handling Spatial Data in
R
2
Classes for Spatial Data in
R
. 21
2.1
Introduction
. 21
2.2
Classes and Methods in
R
. 23
2.3
Spatial Objects
. 28
2.4
SpatialPoints
. 30
2.4.1
Methods
. 31
2.4.2
Data Frames for Spatial Point Data
. 33
2.5
SpatialLines
. 38
X
Contents
2.6 SpatialPolygons. 41
2.6.1 SpatialPolygonsDataFrame
Objects.
44
2.6.2
Holes and Ring Direction
. 46
2.7
SpatialGrid and SpatialPixel Objects
. 47
3
Visualising Spatial Data
. 57
3.1
The Traditional Plot System
. 58
3.1.1
Plotting Points, Lines, Polygons, and Grids
. 58
3.1.2
Axes and Layout Elements
. 60
3.1.3
Degrees in Axes Labels and Reference Grid
. 64
3.1.4
Plot Size, Plotting Area, Map Scale,
and Multiple Plots
. 65
3.1.5
Plotting Attributes and Map Legends
. 66
3.2
Trellis/Lattice Plots with spplot
. 68
3.2.1
A Straight Trellis Example
. 68
3.2.2
Plotting Points, Lines, Polygons, and Grids
. 70
3.2.3
Adding Reference and Layout Elements to Plots
. 72
3.2.4
Arranging Panel Layout
. 73
3.3
Interacting with Plots
. 74
3.3.1
Interacting with Base Graphics
. 74
3.3.2
Interacting with spplot and Lattice Plots
. 76
3.4
Colour Palettes and Class Intervals
. 76
3.4.1
Colour Palettes
. 76
3.4.2
Class Intervals
. 77
4
Spatial Data Import and Export
. 81
4.1
Coordinate Reference Systems
. 82
4.1.1
Using the EPSG List
. 83
4.1.2
PROJ.4 CRS Specification
. 84
4.1.3
Projection and Transformation
. 85
4.1.4
Degrees, Minutes, and Seconds
. 87
4.2
Vector File Formats
. 88
4.2.1
Using OGR Drivers in rgdal
. 89
4.2.2
Other Import/Export Functions
. 93
4.3
Raster File Formats
. 93
4.3.1
Using GDAL Drivers in rgdal
. 94
4.3.2
Writing a Google Earth™ Image Overlay
. 97
4.3.3
Other Import/Export Functions
. 98
4.4
Grass
. 99
4.4.1
Broad Street Cholera Data
.104
4.5
Other Import/Export Interfaces
.106
4.5.1
Analysis and Visualisation Applications
.108
4.5.2
TerraLib and aRT
.108
4.5.3
Other
GIS
and Web Mapping Systems
.110
4.6
Installing rgdal
.
Ill
Contents
XI
Further Methods for Handling Spatial Data
.113
5.1
Support
.113
5.2
Overlay
.116
5.3
Spatial Sampling
.118
5.4
Checking Topologies
.120
5.4.1
Dissolving Polygons
.121
5.4.2
Checking Hole Status
.122
5.5
Combining Spatial Data
.123
5.5.1
Combining Positional Data
.123
5.5.2
Combining Attribute Data
.124
5.6
Auxiliary Functions
.126
Customising Spatial Data Classes and Methods
.127
6.1
Programming with Classes and Methods
.127
6.1.1
ЅЗ
-Style
Classes and Methods
.129
6.1.2
S^Style Classes and Methods
.130
6.2
Animal Track Data in Package Trip
.130
6.2.1
Generic and Constructor Functions
.131
6.2.2
Methods for Trip Objects
.133
6.3
Multi-Point Data: SpatialMultiPoints
.134
6.4
Hexagonal Grids
.137
6.5
Spatio-
Temporal Grids
.140
6.6
Analysing Spatial Monte Carlo Simulations
.144
6.7
Processing Massive Grids
.146
Part II Analysing Spatial Data
7
Spatial Point Pattern Analysis
.155
7.1
Introduction
.155
7.2
Packages for the Analysis of Spatial Point Patterns
.156
7.3
Preliminary Analysis of a Point Pattern
.160
7.3.1
Complete Spatial Randomness
.160
7.3.2
G
Function: Distance to the Nearest Event
.161
7.3.3
F
Function: Distance from a Point
to the Nearest Event
.162
7.4
Statistical Analysis of Spatial Point Processes
.163
7.4.1
Homogeneous
Poisson
Processes
.164
7.4.2
Inhomogeneous
Poisson
Processes
.165
7.4.3
Estimation of the Intensity
.165
7.4.4
Likelihood of an Inhomogeneous
Poisson
Process
.168
7.4.5
Second-Order Properties
.171
7.5
Some Applications in Spatial Epidemiology
.172
7.5.1
Case-Control Studies
.173
7.5.2
Binary Regression Estimator
.178
XII Contents
7.5.3
Binary Regression Using Generalised
Additive Models
.180
7.5.4
Point Source Pollution
.182
7.5.5
Accounting for Confounding and Covariates
.186
7.6
Further Methods for the Analysis of Point Patterns
.190
8
Interpolation and Geostatistics
.191
8.1
Introduction
.191
8.2
Exploratory Data Analysis
.192
8.3
Non-Geostatistical Interpolation Methods
.193
8.3.1
Inverse Distance Weighted Interpolation
.193
8.3.2
Linear Regression
.194
8.4
Estimating Spatial Correlation: The Variogram
.195
8.4.1
Exploratory Variogram Analysis
.196
8.4.2
Cutoff, Lag Width, Direction Dependence
.200
8.4.3
Variogram Modelling
.201
8.4.4
Anisotropy
.205
8.4.5 Multivariable
Variogram Modelling
.206
8.4.6
Residual Variogram Modelling
.208
8.5
Spatial Prediction
.209
8.5.1
Universal, Ordinary, and Simple Kriging
.209
8.5.2 Multivariable
Prediction: Cokriging
.210
8.5.3
Collocated Cokriging
.212
8.5.4
Cokriging Contrasts
.213
8.5.5
Kriging in a Local Neighbourhood
.213
8.5.6
Change of Support: Block Kriging
.215
8.5.7
Stratifying the Domain
.216
8.5.8
Trend Functions and their Coefficients
.217
8.5.9
Non-Linear Transforms of the Response Variable
.218
8.5.10
Singular Matrix Errors
.220
8.6
Model Diagnostics
.221
8.6.1
Cross Validation Residuals
.222
8.6.2
Cross Validation z-Scores
.223
8.6.3 Multivariable
Cross Validation
.225
8.6.4
Limitations to Cross Validation
.225
8.7
Geostatistical Simulation
.226
8.7.1
Sequential Simulation
.227
8.7.2
Non-Linear Spatial Aggregation and Block Averages
. . 229
8.7.3 Multivariable
and Indicator Simulation
.230
8.8
Model-Based Geostatistics and Bayesian Approaches
.230
8.9
Monitoring Network Optimization
.231
8.10
Other
R
Packages for Interpolation and Geostatistics
.233
8.10.1
Non-Geostatistical Interpolation
.233
8.10.2
spatial
.233
8.10.3
RandomFields
.234
8.10.4
geoR and geoRghn
. .235
8.10.5
fields
. .235
Contents XIII
9 Areal Data and
Spatial
Autocorrelation .
237
9.1
Introduction
.237
9.2
Spatial Neighbours
.239
9.2.1
Neighbour Objects
.240
9.2.2
Creating Contiguity Neighbours
.242
9.2.3
Creating Graph-Based Neighbours
.244
9.2.4
Distance-Based Neighbours
.246
9.2.5
Higher-Order Neighbours
.249
9.2.6
Grid Neighbours
.250
9.3
Spatial Weights
.251
9.3.1
Spatial Weights Styles
.251
9.3.2
General Spatial Weights
.253
9.3.3
Importing, Converting, and Exporting Spatial
Neighbours and Weights
.255
9.3.4
Using Weights to Simulate Spatial Autocorrelation
. 257
9.3.5
Manipulating Spatial Weights
.258
9.4
Spatial Autocorrelation: Tests
.258
9.4.1
Global Tests
.261
9.4.2
Local Tests
.268
10
Modelling
Areal Data .273
10.1
Introduction
.273
10.2
Spatial Statistics Approaches
.274
10.2.1
Simultaneous
Autoregressive
Models
.277
10.2.2
Conditional
Autoregressive
Models
.282
10.2.3
Fitting Spatial Regression Models
.284
10.3
Mixed-Effects Models
.287
10.4
Spatial Econometrics Approaches
.289
10.5
Other Methods
.296
10.5.1
GAM, GEE, GLMM
.297
10.5.2
Moran
Eigenvectors
.302
10.5.3
Geographically Weighted Regression
.305
11
Disease Mapping
.311
11.1
Introduction
.312
11.2
Statistical Models
.314
11.2.1
Poisson-Gamma
Model
.315
11.2.2
Log-Normal Model
.316
11.2.3
Marshall's Global EB Estimator
.318
11.3
Spatially Structured Statistical Models
.319
11.4
Bayesian Hierarchical Models
.321
11.4.1
The
Poisson-Gamma
Model Revisited
.322
11.4.2
Spatial Models
.325
11.5
Detection of Clusters of Disease
.332
11.5.1
Testing the Homogeneity of the Relative Risks
.333
11.5.2
Moran's /Test of Spatial Autocorrelation
.335
XIV Contents
11.5.3
Tango's Test of General Clustering
.335
11.5.4
Detection of the Location of a Cluster
.337
11.5.5
Geographical Analysis Machine
.337
11.5.6
Kulldorff
s
Statistic
.338
11.5.7
Stone's Test for Localised Clusters
.340
11.6
Other Topics in Disease Mapping
.341
Afterword
.343
R
and Package Versions Used
.344
Data Sets Used
.344
References
.347
Subject Index
.361
Functions Index
.371 |
| adam_txt |
Contents
Preface
.
VII
1
Hello World:
Introducing Spatial Data
. 1
1.1
Applied
Spatial Data Analysis
. 1
1.2
Why Do We
Use
R
. 2
1.2.1 .
In General?
. 2
1.2.2 .
for Spatial Data Analysis?
.
З
1.3
R
and GIS
. 4
1.3.1
What is
GIS?
. 4
1.3.2
Service-Oriented Architectures
. 6
1.3.3
Further Reading on
GIS
. 6
1.4
Types of Spatial Data
. 7
1.5
Storage and Display
. 10
1.6
Applied Spatial Data Analysis
. 11
1.7
R
Spatial Resources
. 13
1.7.1
Online Resources
. 14
1.7.2
Layout of the Book
. 14
Part I Handling Spatial Data in
R
2
Classes for Spatial Data in
R
. 21
2.1
Introduction
. 21
2.2
Classes and Methods in
R
. 23
2.3
Spatial Objects
. 28
2.4
SpatialPoints
. 30
2.4.1
Methods
. 31
2.4.2
Data Frames for Spatial Point Data
. 33
2.5
SpatialLines
. 38
X
Contents
2.6 SpatialPolygons. 41
2.6.1 SpatialPolygonsDataFrame
Objects.
44
2.6.2
Holes and Ring Direction
. 46
2.7
SpatialGrid and SpatialPixel Objects
. 47
3
Visualising Spatial Data
. 57
3.1
The Traditional Plot System
. 58
3.1.1
Plotting Points, Lines, Polygons, and Grids
. 58
3.1.2
Axes and Layout Elements
. 60
3.1.3
Degrees in Axes Labels and Reference Grid
. 64
3.1.4
Plot Size, Plotting Area, Map Scale,
and Multiple Plots
. 65
3.1.5
Plotting Attributes and Map Legends
. 66
3.2
Trellis/Lattice Plots with spplot
. 68
3.2.1
A Straight Trellis Example
. 68
3.2.2
Plotting Points, Lines, Polygons, and Grids
. 70
3.2.3
Adding Reference and Layout Elements to Plots
. 72
3.2.4
Arranging Panel Layout
. 73
3.3
Interacting with Plots
. 74
3.3.1
Interacting with Base Graphics
. 74
3.3.2
Interacting with spplot and Lattice Plots
. 76
3.4
Colour Palettes and Class Intervals
. 76
3.4.1
Colour Palettes
. 76
3.4.2
Class Intervals
. 77
4
Spatial Data Import and Export
. 81
4.1
Coordinate Reference Systems
. 82
4.1.1
Using the EPSG List
. 83
4.1.2
PROJ.4 CRS Specification
. 84
4.1.3
Projection and Transformation
. 85
4.1.4
Degrees, Minutes, and Seconds
. 87
4.2
Vector File Formats
. 88
4.2.1
Using OGR Drivers in rgdal
. 89
4.2.2
Other Import/Export Functions
. 93
4.3
Raster File Formats
. 93
4.3.1
Using GDAL Drivers in rgdal
. 94
4.3.2
Writing a Google Earth™ Image Overlay
. 97
4.3.3
Other Import/Export Functions
. 98
4.4
Grass
. 99
4.4.1
Broad Street Cholera Data
.104
4.5
Other Import/Export Interfaces
.106
4.5.1
Analysis and Visualisation Applications
.108
4.5.2
TerraLib and aRT
.108
4.5.3
Other
GIS
and Web Mapping Systems
.110
4.6
Installing rgdal
.
Ill
Contents
XI
Further Methods for Handling Spatial Data
.113
5.1
Support
.113
5.2
Overlay
.116
5.3
Spatial Sampling
.118
5.4
Checking Topologies
.120
5.4.1
Dissolving Polygons
.121
5.4.2
Checking Hole Status
.122
5.5
Combining Spatial Data
.123
5.5.1
Combining Positional Data
.123
5.5.2
Combining Attribute Data
.124
5.6
Auxiliary Functions
.126
Customising Spatial Data Classes and Methods
.127
6.1
Programming with Classes and Methods
.127
6.1.1
ЅЗ
-Style
Classes and Methods
.129
6.1.2
S^Style Classes and Methods
.130
6.2
Animal Track Data in Package Trip
.130
6.2.1
Generic and Constructor Functions
.131
6.2.2
Methods for Trip Objects
.133
6.3
Multi-Point Data: SpatialMultiPoints
.134
6.4
Hexagonal Grids
.137
6.5
Spatio-
Temporal Grids
.140
6.6
Analysing Spatial Monte Carlo Simulations
.144
6.7
Processing Massive Grids
.146
Part II Analysing Spatial Data
7
Spatial Point Pattern Analysis
.155
7.1
Introduction
.155
7.2
Packages for the Analysis of Spatial Point Patterns
.156
7.3
Preliminary Analysis of a Point Pattern
.160
7.3.1
Complete Spatial Randomness
.160
7.3.2
G
Function: Distance to the Nearest Event
.161
7.3.3
F
Function: Distance from a Point
to the Nearest Event
.162
7.4
Statistical Analysis of Spatial Point Processes
.163
7.4.1
Homogeneous
Poisson
Processes
.164
7.4.2
Inhomogeneous
Poisson
Processes
.165
7.4.3
Estimation of the Intensity
.165
7.4.4
Likelihood of an Inhomogeneous
Poisson
Process
.168
7.4.5
Second-Order Properties
.171
7.5
Some Applications in Spatial Epidemiology
.172
7.5.1
Case-Control Studies
.173
7.5.2
Binary Regression Estimator
.178
XII Contents
7.5.3
Binary Regression Using Generalised
Additive Models
.180
7.5.4
Point Source Pollution
.182
7.5.5
Accounting for Confounding and Covariates
.186
7.6
Further Methods for the Analysis of Point Patterns
.190
8
Interpolation and Geostatistics
.191
8.1
Introduction
.191
8.2
Exploratory Data Analysis
.192
8.3
Non-Geostatistical Interpolation Methods
.193
8.3.1
Inverse Distance Weighted Interpolation
.193
8.3.2
Linear Regression
.194
8.4
Estimating Spatial Correlation: The Variogram
.195
8.4.1
Exploratory Variogram Analysis
.196
8.4.2
Cutoff, Lag Width, Direction Dependence
.200
8.4.3
Variogram Modelling
.201
8.4.4
Anisotropy
.205
8.4.5 Multivariable
Variogram Modelling
.206
8.4.6
Residual Variogram Modelling
.208
8.5
Spatial Prediction
.209
8.5.1
Universal, Ordinary, and Simple Kriging
.209
8.5.2 Multivariable
Prediction: Cokriging
.210
8.5.3
Collocated Cokriging
.212
8.5.4
Cokriging Contrasts
.213
8.5.5
Kriging in a Local Neighbourhood
.213
8.5.6
Change of Support: Block Kriging
.215
8.5.7
Stratifying the Domain
.216
8.5.8
Trend Functions and their Coefficients
.217
8.5.9
Non-Linear Transforms of the Response Variable
.218
8.5.10
Singular Matrix Errors
.220
8.6
Model Diagnostics
.221
8.6.1
Cross Validation Residuals
.222
8.6.2
Cross Validation z-Scores
.223
8.6.3 Multivariable
Cross Validation
.225
8.6.4
Limitations to Cross Validation
.225
8.7
Geostatistical Simulation
.226
8.7.1
Sequential Simulation
.227
8.7.2
Non-Linear Spatial Aggregation and Block Averages
. . 229
8.7.3 Multivariable
and Indicator Simulation
.230
8.8
Model-Based Geostatistics and Bayesian Approaches
.230
8.9
Monitoring Network Optimization
.231
8.10
Other
R
Packages for Interpolation and Geostatistics
.233
8.10.1
Non-Geostatistical Interpolation
.233
8.10.2
spatial
.233
8.10.3
RandomFields
.234
8.10.4
geoR and geoRghn
. .235
8.10.5
fields
. .235
Contents XIII
9 Areal Data and
Spatial
Autocorrelation .
237
9.1
Introduction
.237
9.2
Spatial Neighbours
.239
9.2.1
Neighbour Objects
.240
9.2.2
Creating Contiguity Neighbours
.242
9.2.3
Creating Graph-Based Neighbours
.244
9.2.4
Distance-Based Neighbours
.246
9.2.5
Higher-Order Neighbours
.249
9.2.6
Grid Neighbours
.250
9.3
Spatial Weights
.251
9.3.1
Spatial Weights Styles
.251
9.3.2
General Spatial Weights
.253
9.3.3
Importing, Converting, and Exporting Spatial
Neighbours and Weights
.255
9.3.4
Using Weights to Simulate Spatial Autocorrelation
. 257
9.3.5
Manipulating Spatial Weights
.258
9.4
Spatial Autocorrelation: Tests
.258
9.4.1
Global Tests
.261
9.4.2
Local Tests
.268
10
Modelling
Areal Data .273
10.1
Introduction
.273
10.2
Spatial Statistics Approaches
.274
10.2.1
Simultaneous
Autoregressive
Models
.277
10.2.2
Conditional
Autoregressive
Models
.282
10.2.3
Fitting Spatial Regression Models
.284
10.3
Mixed-Effects Models
.287
10.4
Spatial Econometrics Approaches
.289
10.5
Other Methods
.296
10.5.1
GAM, GEE, GLMM
.297
10.5.2
Moran
Eigenvectors
.302
10.5.3
Geographically Weighted Regression
.305
11
Disease Mapping
.311
11.1
Introduction
.312
11.2
Statistical Models
.314
11.2.1
Poisson-Gamma
Model
.315
11.2.2
Log-Normal Model
.316
11.2.3
Marshall's Global EB Estimator
.318
11.3
Spatially Structured Statistical Models
.319
11.4
Bayesian Hierarchical Models
.321
11.4.1
The
Poisson-Gamma
Model Revisited
.322
11.4.2
Spatial Models
.325
11.5
Detection of Clusters of Disease
.332
11.5.1
Testing the Homogeneity of the Relative Risks
.333
11.5.2
Moran's /Test of Spatial Autocorrelation
.335
XIV Contents
11.5.3
Tango's Test of General Clustering
.335
11.5.4
Detection of the Location of a Cluster
.337
11.5.5
Geographical Analysis Machine
.337
11.5.6
Kulldorff
s
Statistic
.338
11.5.7
Stone's Test for Localised Clusters
.340
11.6
Other Topics in Disease Mapping
.341
Afterword
.343
R
and Package Versions Used
.344
Data Sets Used
.344
References
.347
Subject Index
.361
Functions Index
.371 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Bivand, Roger 1951- Pebesma, Edzer J. 1967- Gómez-Rubio, Virgilio |
| author_GND | (DE-588)109813561 (DE-588)136857736 (DE-588)135987407 |
| author_facet | Bivand, Roger 1951- Pebesma, Edzer J. 1967- Gómez-Rubio, Virgilio |
| author_role | aut aut aut |
| author_sort | Bivand, Roger 1951- |
| author_variant | r b rb e j p ej ejp v g r vgr |
| building | Verbundindex |
| bvnumber | BV023471109 |
| classification_rvk | RB 10103 RB 10104 SK 850 ST 250 ST 601 |
| classification_tum | GEO 007f DAT 307f |
| ctrlnum | (OCoLC)441810785 (DE-599)DNB988178907 |
| dewey-full | 519.50285 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.50285 |
| dewey-search | 519.50285 |
| dewey-sort | 3519.50285 |
| dewey-tens | 510 - Mathematics |
| discipline | Geowissenschaften Informatik Mathematik Geographie |
| discipline_str_mv | Geowissenschaften Informatik Mathematik Geographie |
| format | Book |
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| id | DE-604.BV023471109 |
| illustrated | Illustrated |
| index_date | 2024-07-02T21:34:26Z |
| indexdate | 2024-07-20T09:46:44Z |
| institution | BVB |
| isbn | 9780387781709 9780387781716 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016653554 |
| oclc_num | 441810785 |
| open_access_boolean | |
| owner | DE-20 DE-703 DE-945 DE-824 DE-11 DE-384 DE-19 DE-BY-UBM DE-188 DE-521 DE-M49 DE-BY-TUM DE-Grf2 |
| owner_facet | DE-20 DE-703 DE-945 DE-824 DE-11 DE-384 DE-19 DE-BY-UBM DE-188 DE-521 DE-M49 DE-BY-TUM DE-Grf2 |
| physical | XIV, 374 S. Ill., graph. Darst., Kt. 235 mm x 155 mm |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | Springer |
| record_format | marc |
| series2 | Use R! |
| spelling | Bivand, Roger 1951- Verfasser (DE-588)109813561 aut Applied spatial data analysis with R Roger S. Bivand ; Edzer J. Pebesma ; Virgilio Gómez-Rubio New York, NY Springer 2008 XIV, 374 S. Ill., graph. Darst., Kt. 235 mm x 155 mm txt rdacontent n rdamedia nc rdacarrier Use R! Datenverarbeitung R (Computer program language) Spatial analysis (Statistics) Data processing R Programm (DE-588)4705956-4 gnd rswk-swf Datenanalyse (DE-588)4123037-1 gnd rswk-swf Raumdaten (DE-588)4206012-6 gnd rswk-swf Raumdaten (DE-588)4206012-6 s Datenanalyse (DE-588)4123037-1 s R Programm (DE-588)4705956-4 s DE-604 Pebesma, Edzer J. 1967- Verfasser (DE-588)136857736 aut Gómez-Rubio, Virgilio Verfasser (DE-588)135987407 aut Erscheint auch als Online-Ausgabe 10.1007/978-0-387-78171-6 text/html http://deposit.dnb.de/cgi-bin/dokserv?id=3087668&prov=M&dok_var=1&dok_ext=htm Inhaltstext Digitalisierung UB Bayreuth application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016653554&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Bivand, Roger 1951- Pebesma, Edzer J. 1967- Gómez-Rubio, Virgilio Applied spatial data analysis with R Datenverarbeitung R (Computer program language) Spatial analysis (Statistics) Data processing R Programm (DE-588)4705956-4 gnd Datenanalyse (DE-588)4123037-1 gnd Raumdaten (DE-588)4206012-6 gnd |
| subject_GND | (DE-588)4705956-4 (DE-588)4123037-1 (DE-588)4206012-6 |
| title | Applied spatial data analysis with R |
| title_auth | Applied spatial data analysis with R |
| title_exact_search | Applied spatial data analysis with R |
| title_exact_search_txtP | Applied spatial data analysis with R |
| title_full | Applied spatial data analysis with R Roger S. Bivand ; Edzer J. Pebesma ; Virgilio Gómez-Rubio |
| title_fullStr | Applied spatial data analysis with R Roger S. Bivand ; Edzer J. Pebesma ; Virgilio Gómez-Rubio |
| title_full_unstemmed | Applied spatial data analysis with R Roger S. Bivand ; Edzer J. Pebesma ; Virgilio Gómez-Rubio |
| title_short | Applied spatial data analysis with R |
| title_sort | applied spatial data analysis with r |
| topic | Datenverarbeitung R (Computer program language) Spatial analysis (Statistics) Data processing R Programm (DE-588)4705956-4 gnd Datenanalyse (DE-588)4123037-1 gnd Raumdaten (DE-588)4206012-6 gnd |
| topic_facet | Datenverarbeitung R (Computer program language) Spatial analysis (Statistics) Data processing R Programm Datenanalyse Raumdaten |
| url | http://deposit.dnb.de/cgi-bin/dokserv?id=3087668&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016653554&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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