Bug fix in intensity.zclustermodel

Author: baddstats

DESCRIPTION

@@ -1,5 +1,5 @@
 Package: spatstat.model
-Version: 3.3-5.001
+Version: 3.3-5.002
 Date: 2025-04-18
 Title: Parametric Statistical Modelling and Inference for the 'spatstat' Family
 Authors@R: c(person("Adrian", "Baddeley", 

NAMESPACE

@@ -636,6 +636,7 @@ export("simulate.mppm")
 export("simulate.ppm")
 export("simulate.profilepl")
 export("simulate.slrm")
+export("simulate.zclustermodel")
 export("slrAssemblePixelData")
 export("slrm")
 export("slrmInfluence")
@@ -1109,6 +1110,7 @@ S3method("shift", "msr")
   S3method("simulate", "ppm")
 S3method("simulate", "profilepl")
   S3method("simulate", "slrm")
+ S3method("simulate", "zclustermodel")
  S3method("Smooth", "influence.ppm")
  S3method("Smooth", "leverage.ppm")
  S3method("Smooth", "msr")

NEWS

@@ -1,10 +1,22 @@
 
-        CHANGES IN spatstat.model VERSION 3.3-5.001
+        CHANGES IN spatstat.model VERSION 3.3-5.002
 
 OVERVIEW
 
-    o Documentation improvements.
+    o Simulation of 'zclustermodel' objects.
 
+    o Documentation improvements and bug fixes.
+    
+NEW FUNCTIONS
+
+    o simulate.zclustermodel
+    Method for simulating objects of class 'zclustermodel'.
+    
+BUG FIXES
+
+    o intensity.zclustermodel
+    Always returned the value zero.
+    Fixed.
 
         CHANGES IN spatstat.model VERSION 3.3-5
 

R/simulatekppm.R

@@ -150,7 +150,8 @@ condSimCox <- function(object, nsim=1,
                        giveup=1000, maxchunk=100,
                        saveLambda=FALSE,
                        verbose=TRUE, drop=FALSE) {
-  stopifnot(is.kppm(object))
+  if(!inherits(object, c("kppm", "zclustermodel")))
+    stop("object should belong to class 'kppm' or 'zclustermodel'", call=FALSE)
   shortcut <- isFALSE(object$isPCP)
 
   w.sim <- as.owin(window)

R/zclustermodel.R

@@ -3,7 +3,7 @@
 #'
 #' Experimental
 #' 
-#'   $Revision: 1.11 $ $Date: 2023/09/11 04:13:58 $
+#'   $Revision: 1.12 $ $Date: 2025/04/18 08:13:38 $
 #'
 
 zclustermodel <- function(name="Thomas", ..., mu, kappa, scale) {
@@ -83,7 +83,7 @@ Kmodel.zclustermodel <- function(model, ...) {
 }
 
 intensity.zclustermodel <- function(X, ...) {
-  X$par[["kappa"]] * X$mu
+  X$par.std[["kappa"]] * X$mu
 }
 
 predict.zclustermodel <- function(object, ...,
@@ -122,3 +122,57 @@ reach.zclustermodel <- function(x, ..., epsilon) {
 }
 
 is.poissonclusterprocess.zclustermodel <- function(model) { TRUE }
+
+simulate.zclustermodel <- function(object, nsim=1, ..., win=unit.square()) {
+  with(object, {
+    switch(name,
+         Thomas = {
+           rThomas(kappa=par.std[["kappa"]],
+                   scale=par.std[["scale"]],
+                   mu=mu,
+                   win=win,
+                   nsim=nsim,
+                   ...)
+         },
+         MatClust = {
+           rMatClust(kappa=par.std[["kappa"]],
+                     scale=par.std[["scale"]],
+                     mu=mu,
+                     win=win,
+                     nsim=nsim,
+                     ...)
+         },
+         Cauchy = {
+           rCauchy(kappa=par.std[["kappa"]],
+                   scale=par.std[["scale"]],
+                   mu=mu,
+                   win=win,
+                   nsim=nsim,
+                   ...)
+         },
+         VarGamma = {
+           do.call(rVarGamma,
+                   resolve.defaults(
+                     list(kappa=par.std[["kappa"]],
+                          scale=par.std[["scale"]],
+                          mu=mu,
+                          win=win,
+                          nsim=nsim,
+                          ...),
+                     clustargs))
+         },
+         LGCP = {
+           do.call(rLGCP,
+                   resolve.defaults(
+                     list(kappa=par.std[["kappa"]],
+                          scale=par.std[["scale"]],
+                          mu=mu,
+                          win=win,
+                          nsim=nsim,
+                          ...),
+                     clustargs))
+         },
+         stop(paste("Unrecognised model name", sQuote(object$name)),
+              call.=FALSE)
+         )})
+}

inst/doc/packagesizes.txt

@@ -19,4 +19,4 @@ date version nhelpfiles nobjects ndatasets Rlines srclines
 "2024-11-19" "3.3-3" 269 726 0 39066 1155
 "2025-01-20" "3.3-4" 269 726 0 39070 1155
 "2025-03-22" "3.3-5" 269 726 0 39076 1155
-"2025-04-18" "3.3-5.001" 269 726 0 39076 1155
+"2025-04-18" "3.3-5.002" 269 727 0 39131 1155

inst/info/packagesizes.txt

@@ -19,4 +19,4 @@ date version nhelpfiles nobjects ndatasets Rlines srclines
 "2024-11-19" "3.3-3" 269 726 0 39066 1155
 "2025-01-20" "3.3-4" 269 726 0 39070 1155
 "2025-03-22" "3.3-5" 269 726 0 39076 1155
-"2025-04-18" "3.3-5.001" 269 726 0 39076 1155
+"2025-04-18" "3.3-5.002" 269 727 0 39131 1155

man/methods.zclustermodel.Rd

@@ -7,6 +7,7 @@
 \alias{print.zclustermodel}
 \alias{clusterradius.zclustermodel}
 \alias{reach.zclustermodel}
+\alias{simulate.zclustermodel}
 \title{
   Methods for Cluster Models
 }
@@ -28,6 +29,8 @@
  \method{clusterradius}{zclustermodel}(model,\dots,thresh=NULL, precision=FALSE)
 
  \method{reach}{zclustermodel}(x, \dots, epsilon)
+
+ \method{simulate}{zclustermodel}(object, nsim=1, \dots, win=unit.square())
 }
 \arguments{
   \item{model,object,x,X}{
@@ -51,6 +54,13 @@
   \item{precision}{
     Logical value stipulating whether the precision should also be returned.
   }
+  \item{win}{
+    Window (object of class \code{"owin"}) in which the simulated
+    pattern should be generated.
+  }
+  \item{nsim}{
+    Number of simulated patterns to be generated.
+  }
 }
 \details{
   Experimental.
@@ -77,6 +87,7 @@
   Z2 <- predict(m2, locations=square(1))
   varcount(m, square(1))
   varcount(m2, square(1))
+  X <- simulate(m)
 }
 \keyword{spatial}
 \keyword{models}