similar to: SPATSTAT: Minimum points for a Ripley K to be sensible?

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 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

Hello everybody-- I have been playing with my data in spatstat, and what I'd like to present is a basic exploratory spatial analysis. I have used the following code, using a ppp.object called tsdspoints. The code develops the simulations and the envelopes I want, but I don't understand my first plot here, the [tsds.ghat.short$r, tsds.ghat.short$raw]...I cobbled together this code

Hi--I'm trying to run a Ripley's K analysis on a point pattern within a window of 1 square km. The maximum distance I want to use is the diagonal of the window, around 1400m, run in 50m increments. The function defaults to a 250m maximum--I thought this was simply the way I had plotted it, but when I exported the data there was nothing over 250m. I've looked into seq and ginterval,

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

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

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

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

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

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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 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

Ranjan Maitra writes: > Does anyone have a suggestion (or better still) code for sampling > from the uniform distribution over the convex hull of a set of > points? This is implemented in library 'spatstat'. If x and y are vectors of coordinates of your initial set of points, library(spatstat) W <- convexhull.xy(x, y) P <- runifpoint(42, W) will compute

Dear R users, I am using spatstat to analyze point patterns (tree locations). I would like to import the shapefile with the study area polygons (six total) into R and use it to create the window for the spatstat analysis. I do not simply want to use a rectangle because the study areas spread out over 40000 ha. Any suggestions would be greatly appreciated. Thanks, Charlotte Reemts Charlotte

I've written the function below to simulate the mean 1st through nth nearest neighbor distances for a random spatial pattern using the functions nndist() and runifpoint() from spatsat. It works, but runs relatively slowly - would appreciate suggestions on how to speed up this function. Thanks. --Dale library(spatstat) sim.nth.mdist <- function(nth,nsim) { D <- matrix(ncol=nth,

Hi, With the following code i can divides window into quadrats and counts the numbers of points in each quadrat. library(spatstat) X <- runifpoint(50) quadratcount(X) quadratcount(X, 4, 5) quadratcount(X, xbreaks=c(0, 0.3, 1), ybreaks=c(0, 0.4, 0.8, 1)) qX <-? quadratcount(X, 4, 5) plot(X) plot(qX, add=TRUE) But I want to mark each? quadrats? and select/ extract only those points by

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 <-

Good day Im working with some coordinates, and want to create a PPP object, I found that error: > Datos=read.table("puntos_texto.txt",dec=".",sep="\t",header=T) > summary(Datos) id y x Min. : 1.0 Min. :1013581 Min. :1177842 1st Qu.: 821.2 1st Qu.:1014442 1st Qu.:1179658 Median

Hello, I am trying to plot a quadratcount object over a ppp object in the spatstat package. I ultimately want to get something like this http://bg9.imslab.co.jp/Rhelp/R-2.4.0/src/library/spatstat/man/images/big_quadratcount_001.png http://bg9.imslab.co.jp/Rhelp/R-2.4.0/src/library/spatstat/man/images/big_quadratcount_001.png See

Hi, I am new to R. I am using spatstat package to generate some sample points but don't know how to save the result to file. Could anyone please give me some instructions? Thanks I generate some random point data by using: pp<-runifpoint(100) I can plot it out with plot(pp) I suppose that pp contains x and y. How can I save these x, y pairs to file that has following format? x1,y1 x2,y2