Spatial point patterns : methodology and applications with R /: methodology and applications with R. (2015)

• Record Type: Book
• Further Information: Note: Adrian Baddeley, Ege Rubak, Rolf Turner.
• Authors: Baddeley, Adrian; Rubak, Ege; Turner, Rolf
• Contents: BASICS; Introduction; Point patterns; Statistical methodology for point patterns; About this book Software Essentials; Introduction to RR; Packages for R; Introduction to spatstat; Getting started with spatstat; FAQ Collecting and Handling Point Pattern Data; Surveys and experiments; Data handling; Entering point pattern data into spatstat; Data errors and quirks; Windows in spatstat; Pixel images in spatstat; Line segment patterns; Collections of objects; Interactive data entry in spatstat; Reading GIS file formats; FAQ Inspecting and Exploring Data; Plotting; Manipulating point patterns and windows; Exploring images; Using line segment patterns; Tessellations; FAQ Point Process Methods; Motivation; Basic definitions; Complete spatial randomness; Inhomogeneous Poisson process; A menagerie of models; Fundamental issues; Goals of analysis EXPLORATORY DATA ANALYSIS; Intensity; Introduction; Estimating homogeneous intensity; Technical definition; Quadrat counting; Smoothing estimation of intensity function; Investigating dependence of intensity on a covariate; Formal tests of (non-)dependence on a covariate; Hot spots, clusters, and local features; Kernel smoothing of marks; FAQ Correlation; Introduction; Manual methods; The K -function; Edge corrections for the K -function; Function objects in spatstat; The pair correlation function; Standard errors and confidence intervals; Testing whether a pattern is completely random; Detecting anisotropy; Adjusting for inhomogeneity; Local indicators of spatial association; Third- and higher-order summary statistics; Theory; FAQ Spacing; Introduction; Basic methods; Nearest-neighbour function G and empty-space function F ; Confidence intervals and simulation envelopes; Empty-space hazard; J -function; Inhomogeneous F -, G - and J -functions; Anisotropy and the nearest-neighbour orientation; Empty-space distance for a spatial pattern; Distance from a point pattern to another spatial pattern; Theory for edge corrections; Palm distribution; FAQ STATISTICAL INFERENCE; Poisson Models; Introduction; Poisson point process models; Fitting Poisson models in spatstat; Statistical inference for Poisson models; Alternative fitting methods; More flexible models; Theory; Coarse quadrature approximation; Fine pixel approximation; Conditional logistic regression; Approximate Bayesian inference; Non-loglinear models; Local likelihood; FAQ Hypothesis Tests and Simulation Envelopes; Introduction; Concepts and terminology; Testing for a covariate effect in a parametric model; Quadrat counting tests; Tests based on the cumulative distribution function; Monte Carlo tests; Monte Carlo tests based on summary functions; Envelopes in spatstat; Other presentations of envelope tests; Dao-Genton test and envelopes; Power of tests based on summary functions; FAQ Model Validation; Overview of validation techniques; Relative intensity; Residuals for Poisson processes; Partial residual plots; Added variable plots; Validating the independence assumption; Leverage and influence; Theory for leverage and influence; FAQ Cluster and Cox Models; Introduction; Cox processes; Cluster processes; Fitting Cox and cluster models to data; Locally fitted models; Theory; FAQ Gibbs Models; Introduction; Conditional intensity; Key concepts; Statistical insights; Fitting Gibbs models to data; Pairwise interaction models; Higher-order interactions; Hybrids of Gibbs models; Simulation; Goodness-of-fit and validation for fitted Gibbs models ; Locally fitted models; Theory: Gibbs processes; Theory: Fitting Gibbs models; Determinantal point processes; FAQ Patterns of Several Types of Points; Introduction; Methodological issues; Handling multitype point pattern data; Exploratory analysis of intensity; Multitype Poisson models; Correlation and spacing; Tests of randomness and independence; Multitype Gibbs models; Hierarchical interactions; Multitype Cox and cluster processes; Other multitype processes; Theory; FAQ ADDITIONAL STRUCTURE; Higher-Dimensional Spaces and Marks; Introduction; Point patterns with numerical or multidimensional marks; Three-dimensional point patterns; Point patterns with any kinds of marks and coordinates; FAQ Replicated Point Patterns and Designed Experiments; Introduction; Methodology; Lists of objects; Hyperframes; Computing with hyperframes; Replicated point pattern datasets in spatstat; Exploratory data analysis; Analysing summary functions from replicated patterns; Poisson models; Gibbs models; Model validation; Theory; FAQ Point Patterns on a Linear Network; Introduction; Network geometry; Data handling; Intensity; Poisson models; Intensity on a tree; Pair correlation function; K -function; FAQ
• Edition: 1st
• Publisher Details: Boca Raton : Chapman & Hall/CRC
• Publication Date: 2015
• Extent: 1 online resource, illustrations (black and white)
• Subjects: 519.23; Spatial analysis (Statistics); Point processes; R (Computer program language)
• Languages: English
• ISBNs: 9781482210217
• Related ISBNs: 9781482210200
• Notes: Note: Description based on CIP data; item not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.