CRAN/E | spatstat.core

spatstat.core

Core Functionality of the 'spatstat' Family

Installation

About

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, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, 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, Neyman-Scott cluster processes, and determinantal point processes. Models may involve dependence on covariates, inter-point 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 Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots.

Citation spatstat.core citation info
spatstat.org/
Bug report File report

Key Metrics

Version 2.4-4
R ≥ 3.5.0
Published 2022-05-18 680 days ago
Needs compilation? yes
License GPL-2
License GPL-3
CRAN checks spatstat.core results

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Maintainer

Maintainer

Adrian Baddeley

Adrian.Baddeley@curtin.edu.au

Authors

Adrian Baddeley

aut / cre

Rolf Turner

aut

Ege Rubak

aut

Kasper Klitgaard Berthelsen

ctb

Achmad Choiruddin

ctb

Jean-Francois 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

Marie-Colette van Lieshout

ctb

Greg McSwiggan

ctb

Tuomas Rajala

ctb

Suman Rakshit

ctb

Dominic Schuhmacher

ctb

Rasmus Plenge Waagepetersen

ctb

Hangsheng Wang

ctb

Material

NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

spatstat.core archive

Depends

R ≥ 3.5.0
spatstat.data ≥ 2.1-0
spatstat.geom ≥2.4-0
spatstat.random ≥ 2.2-0
stats
graphics
grDevices
utils
methods
nlme
rpart

Imports

spatstat.utils ≥ 2.3-1
spatstat.sparse ≥ 2.0-0
mgcv
Matrix
abind
tensor
goftest ≥ 1.2-2

Suggests

sm
maptools ≥ 0.9-9
gsl
locfit
spatial
RandomFields ≥ 3.1.24.1
RandomFieldsUtils ≥ 0.3.3.1
fftwtools ≥0.9-8
nleqslv
spatstat.linnet ≥ 2.0-0
spatstat ≥2.3-3

Reverse Depends

dbmss
globalKinhom
ppmlasso
spatstat
spatstat.gui
spatstat.Knet
spatstat.linnet
spatstat.local

Reverse Imports

Biolinv
DRHotNet
ecespa
ETAS
ForestGapR
geonet
GmAMisc
hht
highriskzone
idar
IDSpatialStats
lacunaritycovariance
lgcp
lisaClust
onpoint
osmplotr
rcarbon
replicatedpp2w
selectspm
Seurat
shar
smacpod
sparr
SpatEntropy
spatialEco
spatialTIME
SpatialVx
spatsurv
spicyR
SpNetPrep
SPUTNIK
stlnpp
stpp
treetop
trip
ttbary

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