similar to: Ripley's K function within envelope--how to change the maximum distance?

Hello, I am writing cause I have a problem when try to create confidence envelopes in spatstat. I have a point data representing firms in my study area. When I try to create confidence envelopes the error message turns up: [> p <- envelope(point, fun=Kest, nsim=99) Error in marks.ppp(Y, dfok = FALSE) : Sorry, not implemented when the marks are a data frame] Could you write me how can I

Hi I looked, but I didn't find it: I need an array [0 to 101] where each element is a list (the result of Kest in spatstat). I.e. I want to do: A[2] <- Kest(pp1) A[3] <- Kest(pp2) ... A[101] <- Kest(pp100) How can I create A ? Rainer -- Rainer M. Krug, Dipl. Phys. (Germany), MSc Conservation Biology (UCT) Department of Conservation Ecology University of Stellenbosch Matieland

Hello! I am writing you because I could not plot the confidence envelopes for functions Jest, Jcross, Jdot, Jmulti, and L, using the Spatstat package. I have already understood how to do that for Kest or Jest, that is: JEnv <- plot(envelope(PPPData, Jest)) Where PPPData is my ppp object. However, for Jcross I must specify the two marks I want to analyse. That is, usually I would get the

Hi I'm working with the function Kest in the package SpatStat (under LINUX with R 2.1.0). In order to evaluate the statistical significance of my point pattern I'm doing 999 Montecarlo replications. The script that use the Kest function runs OK for most of the different point patterns that I have but for a particular point pattern, which have only 17 points, it runs until the 34th

Hi I have the following loop and would like to vectorize it. Any ideas if it is possible? Thanks, Rainer Tha Loop: for (i in 2:Result$NoSims) { ppp <- runifpoint(Result$NoPlants) K <- Kest(ppp) Result$LSim[i,] <- sqrt(K$iso / pi) - K$r CM <- (Result$LSim[i,] * Result$LSim[i,]) / abs(K$r[2] - K$r[1]) Result$SigCM[i] <- sum(CM, na.rm=TRUE) print(i) flush.console() }

Hi R users, This query is regarding the use of the 'envelope' function in Spatstat. My data can be represented as a point process with CONTINUOUS marks: points <- ppp(x=x,y=y, marks=m, window= wind) However the marks are alignments (lines), and so have to be treated differently to normal scalar marks. Hence to create a mcf object with the appropriate test function for alignment

hi! I did Riply's K function and envelope in the package "SPATSTAT". When the species number is less, it can work well and it is quickly. But when the species number is more(example:2000), it told me"memory limit". So I change "memory limit". But the speed is very slow. I took 13 hours to run the programe. Perhaps there are other methods that can do it. Or just

Dear R-helpers, After putting my somewhat sparse (21 points) data into a 'ppp' format, I am unable to calculate the K function using Kest. I get the error "some 'x' not counted; maybe 'breaks' do not span range of 'x' ". So I tried to calculate the K function using the swedishpines dataset. Of course Kest(swedishpines) works fine but when i break it

Hi I have a loop which is doing time consuming calculations and I would like to be able to have some feedback on where it is in it's calculations. I tried to simply show the counter variable in the loop, but id doesn't work as all display seems to be delayed until the loop is completed. Is there any way of displaying the progress of a loop? Rainer The loop: for (i in

Hi All! As a new useR, I am currently working in R 2.5.1 to produce Ripley's L (the linear version of Ripley's K) for a spatial point dataset (originally a ESRI shapefile). I have coerced the data to a ppp object (because I was originally using 'kest' in the spstat package to produced Ripley's K) but I need to convert my spatial data to a spp object to be able to use

Hello, What are the minimum number of points in a point pattern before a clustering analysis using a Ripley K function loses any meaning? I haven't been able to find much comment in the literature about this --- instead case examples typically use 100-200 points as a minimum. Regards, Sebastian Pucilowski

Hi, R-users, I met a problem: Items:[Anna 'moi =) akku loppu joskus 4ltä. Kestää kauan nää..'\tAmer, Tuusula (0:20)\t20\t12\t16\t00\t00\t11]/Anne 'Ei jakoa,uus päivä muistio et 4n niin peruin. Hups'\t (0:16)\t0\t12\t18\t00\t00\t11/Elina 'Konsertissa. En tod. vastaa teille'\tEtu-Töölö, Helsinki (2:40)\t24\t12\t18\t00\t00\t11 I want to parsing the above data into the

I have spatial data on various species of trees within plots. What I'd like to know is if their patterns are positively associated or not. Could I use cor.test on the values generated by Kest or Gest functions? or would it be more powerful to do a G i to j and then G j to i analysis instead? Thanks, Suzie __________________________________________________________________ Switch to Netscape

Hi, I am trying to test the random labeling hypothesis with my data. I have a point pattern of bird nests and each nest has a mark that it is either predated or not-predated. I want to test the null hypothesis that the K distribution of predation events is equal to the K distribution of all events (nests). This is the code I am using: Kdif <- function(X,...,i) { Kidot <-

Dear All, I have a collections of spatial data. I have to analyze pairs of these point patterns to test their spatial interaction. I was moving towards the cross K Ripley's function. The problem, however, are the following: 1) What is the best way to get a single real value that represents the interaction "power"? 2) How to obtain a value that even allows me to rank the pairwise

I have plotted Ripley's K function for a spatial point pattern for 12 plots, with 39 Monte Carlo simulations for complete spatial randomness (CSR). I would like to analyse these data as follows: I would like to know for which plots the Ripley's K function deviates from CSR at a number of confidence intervals, namely 90%, 95% and 99%. I realise that simulation envelope I have produced

Dear friends, I am studying the spatial distribution of trees in a tropical swamp forest in Brazil, and the spatial association between the trees and other forest and non forest elements. These are point pattern analysis of mapped data, preferentially done with the L function of Ripley. I have recently discovererd the R-project and would like to know whether it is possible to do these

Hi I want to install eda library. Where can I download it? I use R version 2.1.0 on Linux. Thanks. Stephen. ----- Original Message ----- From: Luis Ridao Cruz <Luisr at frs.fo> Date: Tuesday, September 13, 2005 1:32 pm Subject: Re: [R] How to erase objects > ?rm > > > >>> <v.schlecht at arcor.de> 13/09/2005 12:08:55 >>> > > Hi, I admit that

Hello, I have used the univariate Ripley K function in R, but does anyone know if there is a bivariate function built in? I have two species that I am dealing with. Also, how might I add error bars into the graphs (univariate and/or bivariate)? Thank you, Karin Leiderman k_leiderman at hotmail.com Graduate Student/Research Assistant Department of Mathematics Univesity of New Mexico

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