Revision f6c1811e0b8755c851c04178019e0c07db04e697 authored by Adrian Baddeley on 22 December 2016, 09:53:41 UTC, committed by cran-robot on 22 December 2016, 09:53:41 UTC
1 parent 1b6f7ce
DESCRIPTION
Package: spatstat
Version: 1.48-0
Nickname: Model Prisoner
Date: 2016-12-22
Title: Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests
Author: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>,
Rolf Turner <r.turner@auckland.ac.nz>
and Ege Rubak <rubak@math.aau.dk>,
with substantial contributions of code by
Kasper Klitgaard Berthelsen;
Ottmar Cronie;
Yongtao Guan;
Ute Hahn;
Abdollah Jalilian;
Marie-Colette van Lieshout;
Tuomas Rajala;
Suman Rakshit;
Dominic Schuhmacher;
Rasmus Waagepetersen;
and Hangsheng Wang.
Additional contributions
by M. Adepeju;
C. Anderson;
Q.W. Ang;
M. Austenfeld;
S. Azaele;
M. Baddeley;
C. Beale;
M. Bell;
R. Bernhardt;
T. Bendtsen;
A. Bevan;
B. Biggerstaff;
A. Bilgrau;
L. Bischof;
C. Biscio;
R. Bivand;
J.M. Blanco Moreno;
F. Bonneu;
J. Burgos;
S. Byers;
Y.M. Chang;
J.B. Chen;
I. Chernayavsky;
Y.C. Chin;
B. Christensen;
J.-F. Coeurjolly;
K. Colyvas;
R. Corria Ainslie;
M. de la Cruz;
P. Dalgaard;
M. D'Antuono;
S. Das;
T. Davies;
P.J. Diggle;
P. Donnelly;
I. Dryden;
S. Eglen;
A. El-Gabbas;
B. Fandohan;
O. Flores;
E.D. Ford;
P. Forbes;
S. Frank;
J. Franklin;
N. Funwi-Gabga;
O. Garcia;
A. Gault;
J. Geldmann;
M. Genton;
S. Ghalandarayeshi;
J. Gilbey;
J. Goldstick;
P. Grabarnik;
C. Graf;
U. Hahn;
A. Hardegen;
M.B. Hansen;
M. Hazelton;
J. Heikkinen;
M. Hering;
M. Herrmann;
P. Hewson;
K. Hingee;
K. Hornik;
P. Hunziker;
J. Hywood;
R. Ihaka;
C. Icos;
A. Jammalamadaka;
R. John-Chandran;
D. Johnson;
M. Khanmohammadi;
R. Klaver;
P. Kovesi;
M. Kuhn;
J. Laake;
F. Lavancier;
T. Lawrence;
R.A. Lamb;
J. Lee;
G.P. Leser;
H.T. Li;
G. Limitsios;
A. Lister;
B. Madin;
M. Maechler;
J. Marcus;
K. Marchikanti;
R. Mark;
J. Mateu;
P. McCullagh;
U. Mehlig;
F. Mestre;
S. Meyer;
X.C. Mi;
L. De Middeleer;
R.K. Milne;
E. Miranda;
J. Moller;
M. Moradi;
V. Morera Pujol;
E. Mudrak;
G.M. Nair;
N. Najari;
N. Nava;
L.S. Nielsen;
F. Nunes;
J.R. Nyengaard;
J. Oehlschlaegel;
T. Onkelinx;
S. O'Riordan;
E. Parilov;
J. Picka;
N. Picard;
M. Porter;
S. Protsiv;
A. Raftery;
S. Rakshit;
B. Ramage;
P. Ramon;
X. Raynaud,
M. Reiter;
I. Renner;
T.O. Richardson;
B.D. Ripley;
E. Rosenbaum;
B. Rowlingson;
J. Rudokas;
J. Rudge;
C. Ryan;
F. Safavimanesh;
A. Sarkka;
C. Schank;
K. Schladitz;
S. Schutte;
B.T. Scott;
O. Semboli;
F. Semecurbe;
V. Shcherbakov;
G.C. Shen;
P. Shi;
H.-J. Ship;
I.-M. Sintorn;
Y. Song;
M. Spiess;
M. Stevenson;
K. Stucki;
M. Sumner;
P. Surovy;
B. Taylor;
T. Thorarinsdottir;
B. Turlach;
T. Tvedebrink;
K. Ummer;
M. Uppala;
A. van Burgel;
T. Verbeke;
M. Vihtakari;
A. Villers;
F. Vinatier;
S. Voss;
S. Wagner;
H. Wang;
H. Wendrock;
J. Wild;
C. Witthoft;
S. Wong;
M. Woringer;
M.E. Zamboni
and
A. Zeileis.
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>
Depends: R (>= 3.3.0), stats, graphics, grDevices, utils, methods,
nlme, rpart
Imports: mgcv, Matrix, deldir (>= 0.0-21), abind, tensor, polyclip (>=
1.5-0), goftest
Suggests: sm, maptools, gsl, locfit, spatial, rpanel, tkrplot,
RandomFields (>= 3.1.24.1), RandomFieldsUtils(>= 0.3.3.1)
Description: Comprehensive open-source toolbox for analysing Spatial Point Patterns. Focused mainly on two-dimensional point patterns, including multitype/marked points, in any spatial region. Also supports three-dimensional point patterns, space-time point patterns in any number of dimensions, point patterns on a linear network, and patterns of other geometrical objects. Supports spatial covariate data such as pixel images.
Contains over 2000 functions for plotting spatial data, exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference.
Data types include point patterns, line segment patterns, spatial windows, pixel images, tessellations, and linear networks.
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, Diggle-Cressie-Loosmore-Ford, Dao-Genton) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov) 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()). 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.
License: GPL (>= 2)
URL: http://www.spatstat.org
LazyData: true
NeedsCompilation: yes
ByteCompile: true
BugReports: https://github.com/spatstat/spatstat/issues
Packaged: 2016-12-22 04:12:10 UTC; adrian
Repository: CRAN
Date/Publication: 2016-12-22 10:53:41
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