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DESCRIPTION

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Package: spatstat.model
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Version: 3.3-5.002
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Date: 2025-04-19
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Version: 3.3-6
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Date: 2025-04-22
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Title: Parametric Statistical Modelling and Inference for the 'spatstat' Family
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Authors@R: c(person("Adrian", "Baddeley",
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role = c("aut", "cre", "cph"),

NAMESPACE

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export("clusterfield.kppm")
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export("clusterfit")
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export("clusterkernel.kppm")
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export("clusterkernel.zclustermodel")
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export("clusterradius.kppm")
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export("clusterradius.zclustermodel")
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export("coef.dppm")
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S3method("cdf.test", "slrm")
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S3method("clusterfield", "kppm")
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S3method("clusterkernel", "kppm")
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S3method("clusterkernel", "zclustermodel")
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S3method("clusterradius", "kppm")
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S3method("clusterradius", "zclustermodel")
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S3method("coef", "dppm")

NEWS

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CHANGES IN spatstat.model VERSION 3.3-5.002
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CHANGES IN spatstat.model VERSION 3.3-6
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OVERVIEW
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R/clusterprocess.R

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#'
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#' clusterprocess.R
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#'
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#' $Revision: 1.1 $ $Date: 2025/04/19 05:17:27 $
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#' $Revision: 1.2 $ $Date: 2025/05/16 07:14:33 $
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#'
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#' clusterprocess() is defined in spatstat.random

R/simulatekppm.R

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#'
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#' simulate.kppm
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#'
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#' $Revision: 1.13 $ $Date: 2025/04/19 05:23:43 $
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#' $Revision: 1.14 $ $Date: 2025/05/22 05:25:49 $
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simulate.kppm <- function(object, nsim=1, seed=NULL, ...,
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window=NULL, covariates=NULL,
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## conditional simulation
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if(!is.null(n.cond)) {
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## fixed number of points
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out <- condSimCox(object, nsim=nsim, seed=NULL, ...,
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out <- CondSimCox(object, nsim=nsim, seed=NULL, ...,
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win=win, covariates=covariates,
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n.cond=n.cond, w.cond=w.cond,
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verbose=verbose, retry=retry, drop=drop)

R/zclustermodel.R

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#'
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#' Experimental
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#'
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#' $Revision: 1.12 $ $Date: 2025/04/18 08:13:38 $
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#' $Revision: 1.13 $ $Date: 2025/05/16 07:14:43 $
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#'
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zclustermodel <- function(name="Thomas", ..., mu, kappa, scale) {
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)})
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}
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clusterkernel.zclustermodel <- function(model, ...) {
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info <- spatstatClusterModelInfo(model$name)
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k <- info$kernel
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par <- model$par.std
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clustargs <- model$clustargs
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f <- function(x, y=0, ...) { k(par, sqrt(x^2+y^2), margs=clustargs) }
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return(f)
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}
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#' The following methods are for generics defined in spatstat.model
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is.poissonclusterprocess.zclustermodel <- function(model) { TRUE }

inst/doc/packagesizes.txt

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"2024-11-19" "3.3-3" 269 726 0 39066 1155
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"2025-01-20" "3.3-4" 269 726 0 39070 1155
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"2025-03-22" "3.3-5" 269 726 0 39076 1155
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"2025-04-19" "3.3-5.002" 269 729 0 39061 1155
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"2025-04-22" "3.3-6" 269 730 0 39071 1155

inst/info/packagesizes.txt

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"2024-11-19" "3.3-3" 269 726 0 39066 1155
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"2025-01-20" "3.3-4" 269 726 0 39070 1155
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"2025-03-22" "3.3-5" 269 726 0 39076 1155
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"2025-04-19" "3.3-5.002" 269 729 0 39061 1155
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"2025-04-22" "3.3-6" 269 730 0 39071 1155

man/spatstat.model-internal.Rd

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\alias{bt.frame}
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\alias{cannot.update}
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\alias{check.separable}
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\alias{clusterkernel.zclustermodel}
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\alias{coef.summary.kppm}
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\alias{coef.summary.ppm}
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\alias{coef.summary.slrm}
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bigvaluerule(objfun, objargs, startpar, \dots)
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cannot.update(\dots)
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check.separable(dmat, covname, isconstant, fatal)
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\method{clusterkernel}{zclustermodel}(model, \dots)
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\method{coef}{summary.kppm}(object, \dots)
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\method{coef}{summary.ppm}(object, \dots)
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\method{coef}{summary.slrm}(object, \dots)

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