similar to: fit a marked poisson process using a quadrature scheme with 'spatstat'

Hi Everyone, I am trying to figure out the spatstat package for the first time and am having some trouble. Unfortunately, I can't post my data set but I'll hopefully post enough details for some help. I want to model the intensity of a spatial point process using 2 covariates from my data. After reading through the documentation, I have successfully created 2 "ppp" objects. The

Dear all, I'm working with two point patterns (ppp) in spatstat. I turned one of them into a spatial covariate (im) object. After that, I used this im object to fit a Poisson model for the second point pattern, using the covariate layer from the first one. In R, the whole thing looks somewhat like this: my_first.im <- as.im(my_first.ppp) test.ppm <- ppm (my_second.ppp, ~my_first,

Spencer Thanks for your thoughts on this. I did a bit of work and did end up with a method (more a trick), but it did work. I am certain there are better ways to do this, but here is how I resolved the issue. The integral I need to evaluate is \begin{equation} \frac{\int_c^{\infty} p(x|\theta)f(\theta)d\theta} {\int_{-\infty}^{\infty} p(x|\theta)f(\theta)d\theta} \end{equation} Where

Hi I am running analysis with Kcross from the package spatstat and I am getting a message that R can not allocate enough memory for a vector of 900MB. R seems to be running towards the 2GB limit per process. The dataset is not to big (ca 3000 points) but the mask for the points is extremely irregular (a buffer around roads which have been sampled) and I can do trhe analysis if I use a

Hello all, I'm attempting to conduct spatial analysis of trees within a plot. I want to see if the trees are spatially correlated to soil characteristics, say pH, or moisture content. I think one way to do it is with mpl, however, my soil characteristics were not taken at exactly the same locations as my trees and further, the vectors aren't the same length. I'm getting the

I normally use the following code to create a figure displaying the mark correlation function for the point pattern process "A": M<-markcorr(A) plot(M) I have now started to use the following code to perform 1000 Monte Carlo simulations of Complete Spatial Randomness (CSR). It is a Monte Carlo test based on envelopes of the Mark correlation function obtained from simulated point

Hello, I have fitted a Poisson Process model in spatstat using >fit1<-ppm(points, ~elevation, covariates=list(elevation=elevation.im)) This far, everything went well, but I try to simulate the fitted model using the function: >sim1<-rmh(fit1) But I get the error message: "Extracting model information...Evaluating trend...done. Checking arguments..determining simulation

A new version 1.9-5 of the package `spatstat' has been uploaded to CRAN. What it is: ---------- spatstat is a package for analysing spatial data, mainly Spatial Point Patterns. What's in it: ------------ Functions for exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types include point patterns, line segment patterns,

A new version 1.9-5 of the package `spatstat' has been uploaded to CRAN. What it is: ---------- spatstat is a package for analysing spatial data, mainly Spatial Point Patterns. What's in it: ------------ Functions for exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types include point patterns, line segment patterns,

Hello, I have fitted a Log-Gaussian Cox Process on my data but when I try to use "simulate.kppm" of the spatstat package I get this error: Error in rLGCP(model = model, mu = mu, param = param, ..., win = win) : The spatial domain of the pixel image ?mu? does not cover the simulation window ?win? I've used covariates as im, changed the npixel value of the spatstat options to

Hello to all, I am having trouble with intregrating a complicated uni-dimensional function of the following form Phi(x-a_1)*Phi(x-a_2)*...*Phi(x-a_{n-1})*phi(x-a_n). Here n is about 5000, Phi is the cumulative distribution function of standard normal, phi is the density function of standard normal, and x ranges over (-infty,infty). My idea is to to use quadrature to handle this integral. But

I upgraded to R version 2.6.0 yesterday; now I find that I can't load spatstat. I re-installed spatstat (that part seemed to work without complaint) but when I execute > library(spatstat) I get the error message Error in dyn.load(file, ...) : unable to load shared library '/Users/rturner/Rlib/spatstat/libs/ i386/spatstat.so':

Sparc Solaris 8 SunStudio 11 compilers R-2.3.1 spatstat 1.10-1 R-2.3.1 and spatstat were installed using SunStudio11 compilers on a Sparc Solaris 8 machine. No errors were reported in the compilations, however, when I try to load spatstat I get an error: > library(spatstat) Loading required package: mgcv This is mgcv 1.3-20 Error in dyn.load(x, as.logical(local), as.logical(now)) :

Hello R Users, I am trying to do a quadrat count defined by covariate properties in spatstat. I have read my elevation raster into R (from ascii) and converted to class "im" for use in spatstat. Now I have point data of class "ppp" which window is the same extent as the elevation image. I can conveniently plot the image and the points on the image as follows:

Hello R Users, I am trying to do a quadrat count defined by covariate properties in spatstat. I have read my elevation raster into R (from ascii) and converted to class "im" for use in spatstat. Now I have point data of class "ppp" which window is the same extent as the elevation image. I can conveniently plot the image and the points on the image as follows:

Full_Name: Georg Roth Version: R.2.0.1.for Windows OS: Win98 Submission from: (NULL) (134.95.43.165) Using libraries "spatstat" and "sm" on R.2.0.1. under Windows 98 bug 1) the libraries "spatstat" and "sm" are not properly identified by the "library()" command on R.2.0.1. (R for Windows98). the libraryname is shown in upper case

Hi all, Does anybody know any function that performs gaussian adapative quadrature integration of univariate functions? Thanks in advance, Regards, Caio __________________________________________________ [[alternative HTML version deleted]]

Can anyone help me on how to get the nodes and weights of the adaptive quadrature using R. Best wishes Boikanyo. ----- The University of Glasgow, charity number SC004401

Hi all, I am trying to install Spatstat on OpenSUSE 11.1. install.packages("spatstat", dependencies = TRUE) fails on the basis of various compiler packages (full message below). I have gcc version 4.3.2, which should include gfortran and g++ - so I'm not sure what to do! Richard * Installing *source* package ?deldir? ... ** libs gfortran

Hi All, I am trying to use A Gaussian quadrature over the interval (-infty,infty) with weighting function W(x)=exp(-(x-mu)^2/sigma) to estimate an integral. Is there a way to do it in R? Is there a function already implemented which uses such weighting function. I have been searching in the statmode package and I found the function "gauss.quad(100, kind="hermite")" which uses