Functionality for data analysis and modelling of spatial data, mainly spatial point patterns, in the 'spatstat' family of packages. (Excludes analysis of spatial data on a linear network, which is covered by the separate package 'spatstat.linnet'.) Exploratory methods include quadrat counts, Kfunctions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with crossvalidated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chisquared, KolmogorovSmirnov, Monte Carlo, DiggleCressieLoosmoreFord, DaoGenton, twostage Monte Carlo) and tests for covariate effects (CoxBermanWallerLawson, KolmogorovSmirnov, ANOVA) are also supported. Parametric models can be fitted to point pattern data using the functions ppm(), kppm(), slrm(), dppm() similar to glm(). Types of models include Poisson, Gibbs and Cox point processes, NeymanScott cluster processes, and determinantal point processes. Models may involve dependence on covariates, interpoint interaction, cluster formation and dependence on marks. Models are fitted by maximum likelihood, logistic regression, minimum contrast, and composite likelihood methods. A model can be fitted to a list of point patterns (replicated point pattern data) using the function mppm(). The model can include random effects and fixed effects depending on the experimental design, in addition to all the features listed above. Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise(), AIC()) and variable selection (sdr). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and QQ plots, leverage and influence diagnostics, partial residuals, and added variable plots.
Package details 


Author  Adrian Baddeley [aut, cre] (<https://orcid.org/0000000194998382>), Rolf Turner [aut] (<https://orcid.org/0000000155215218>), Ege Rubak [aut] (<https://orcid.org/000000026675533X>), Kasper Klitgaard Berthelsen [ctb], Achmad Choiruddin [ctb], JeanFrancois Coeurjolly [ctb], Ottmar Cronie [ctb], Tilman Davies [ctb], Chiara Fend [ctb], Julian Gilbey [ctb], Yongtao Guan [ctb], Ute Hahn [ctb], Kassel Hingee [ctb], Abdollah Jalilian [ctb], Frederic Lavancier [ctb], MarieColette van Lieshout [ctb], Greg McSwiggan [ctb], Tuomas Rajala [ctb], Suman Rakshit [ctb], Dominic Schuhmacher [ctb], Rasmus Plenge Waagepetersen [ctb], Hangsheng Wang [ctb] 
Maintainer  Adrian Baddeley <Adrian.Baddeley@curtin.edu.au> 
License  GPL (>= 2) 
Version  2.44 
URL  http://spatstat.org/ 
Package repository  View on CRAN 
Installation 
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