fitted.slrm has more features

Author: baddstats

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: spatstat.model
-Version: 3.2-11.010
-Date: 2024-06-28
+Version: 3.2-11.011
+Date: 2024-06-29
 Title: Parametric Statistical Modelling and Inference for the 'spatstat' Family
 Authors@R: c(person("Adrian", "Baddeley", 
                     role = c("aut", "cre", "cph"),

NEWS

@@ -1,11 +1,13 @@
 
-        CHANGES IN spatstat.model VERSION 3.2-11.010
+        CHANGES IN spatstat.model VERSION 3.2-11.011
 
 OVERVIEW
 
     o Package now depends on 'spatstat.univar'.
 
     o Easier control over quadrature schemes.
+
+    o More options in fitted.slrm
 
     o Bug fix in predict.ppm.
 
@@ -21,6 +23,14 @@ SIGNIFICANT USER-VISIBLE CHANGES
     New argument 'quad.args' is a list of arguments passed to 'quadscheme'
     to control the construction of the quadrature scheme.
 
+    o fitted.slrm
+    New argument 'type' allows calculation of fitted probabilities, intensities
+    or link function values.
+
+    o fitted.slrm
+    New arguments 'dataonly' and 'leaveoneout' allow calculation of fitted
+    values at the data points only, using leave-one-out calculation if desired.
+
 BUG FIXES
 
     o predict.ppm

R/slrm.R

@@ -431,10 +431,30 @@ logLik.slrm <- function(object, ..., adjust=TRUE) {
   return(ll)
 }
 
-fitted.slrm <- function(object, ...) {
-  if(length(list(...)) > 0)
-    warning("second argument (and any subsequent arguments) ignored")
-  predict(object, type="probabilities")
+fitted.slrm <- function(object, ..., type="probabilities",
+                        dataonly=FALSE, leaveoneout=FALSE) {
+  trap.extra.arguments(...)
+  ## predict at every pixel
+  Z <- predict(object, type=type)
+  if(!dataonly) {
+    return(Z)
+  }
+  ## require fitted values only at original point locations
+  X <- response(object)
+  if(!leaveoneout) {
+    ## just extract fitted values
+    ZX <- safelookup(Z, X)
+    return(ZX)
+  }
+  ## leave-one-out calculation, directly
+  nX <- npoints(X)
+  ZX <- numeric(nX)
+  for(i in seq_len(nX)) {
+    model.i <- updateData(object, X[-i])
+    Z.i <- predict(model.i)
+    ZX[i] <- safelookup(Z.i, X[i])
+  }
+  return(ZX)
 }
 
 intensity.slrm <- function(X, ...) {

inst/doc/packagesizes.txt

@@ -14,4 +14,4 @@ date version nhelpfiles nobjects ndatasets Rlines srclines
 "2024-02-01" "3.2-9" 269 724 0 39028 1155
 "2024-02-02" "3.2-10" 269 724 0 39028 1155
 "2024-03-22" "3.2-11" 269 724 0 39028 1155
-"2024-06-28" "3.2-11.010" 269 726 0 39031 1155
+"2024-06-29" "3.2-11.011" 269 726 0 39051 1155

inst/info/packagesizes.txt

@@ -14,4 +14,4 @@ date version nhelpfiles nobjects ndatasets Rlines srclines
 "2024-02-01" "3.2-9" 269 724 0 39028 1155
 "2024-02-02" "3.2-10" 269 724 0 39028 1155
 "2024-03-22" "3.2-11" 269 724 0 39028 1155
-"2024-06-28" "3.2-11.010" 269 726 0 39031 1155
+"2024-06-29" "3.2-11.011" 269 726 0 39051 1155

man/fitted.slrm.Rd

@@ -6,10 +6,12 @@
 }
 \description{
   Given a fitted Spatial Logistic Regression model,
-  this function computes the fitted probabilities for each pixel.
+  this function computes the fitted probabilities for each pixel,
+  or the fitted probabilities at each original data point.
 }
 \usage{
-  \method{fitted}{slrm}(object, ...)
+  \method{fitted}{slrm}(object, \dots, type="probabilities",
+                 dataonly=FALSE, leaveoneout=FALSE)
 }
 \arguments{
   \item{object}{
@@ -19,6 +21,23 @@
   \item{\dots}{
     Ignored.
   }
+  \item{type}{
+    Character string (partially) matching one of 
+    \code{"probabilities"}, \code{"intensity"} or \code{"link"}
+    determining the quantity that should be predicted.
+  }
+  \item{dataonly}{
+    Logical. If \code{TRUE}, then values will only be computed
+    at the points of the data point pattern. If \code{FALSE}, then
+    values will be computed at the pixels used to fit the model.
+  }
+  \item{leaveoneout}{
+    Logical value
+    specifying whether to perform a leave-one-out calculation
+    when \code{dataonly=TRUE}. If \code{leaveoneout=TRUE},
+    the fitted value at each data point \code{X[i]} is calculated
+    by re-fitting the model to the data with \code{X[i]} removed.
+  }
 }
 \details{
   This is a method for the generic function
@@ -27,12 +46,18 @@
   (objects of class \code{"slrm"}, usually obtained
   from the function \code{\link{slrm}}).
 
-  The algorithm computes
-  the fitted probabilities of the presence of a random point in each pixel.
+  By default, the algorithm computes
+  the fitted probabilities of the presence of a random point in each
+  pixel,
+  and returns them as an image.
+
+  If \code{dataonly=TRUE}, the algorithm computes the fitted
+  presence probabilities only at the locations of the original data points.
 }
 \value{
   A pixel image (object of class \code{"im"}) containing the
-  fitted probability for each pixel.
+  fitted probability for each pixel,
+  or a numeric vector containing the fitted probability at each data point.
 }
 \seealso{
   \code{\link{slrm}},
@@ -42,6 +67,7 @@
   X <- rpoispp(42)
   fit <- slrm(X ~ x+y)
   plot(fitted(fit))
+  fitted(fit, dataonly=TRUE)
 }
 \author{\adrian
   and \rolf.