search for: kest

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 7602 South Afric...

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'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,...

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 solve this problem please? Thank you Pavel -- View this message in context: http://r.789695.n4.nabble.com/Spatstat-Kest-envelope-problem-tp4657799.html Sent...

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() } -- NEW TELEPHONE NUMBER Tel: +27 - (0)72 808 2975 (w) Rainer M. Krug, Dipl. Phys. (Germany), MSc...

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 down to Kest(ppp (swedishpines$x,swedishpines$...

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 Jcross doing: Jc <- Jcross(PPPData,"Aun","Qsu") For marks "Aun" and &q...

...exported the data there was nothing over 250m. I've looked into seq and ginterval, and I think that seq may be my answer, but I'm not exactly sure how to use it properly within the envelope function. Here's two versions of the code I'm working with: ERip<-envelope(EforRip,fun=Kest,correction=c("Ripley"),nsim=99,rank=1,transform=expression(sqrt(./pi)),global=TRUE) ERip<-envelope(EforRip,fun=Kest,r=seq(0,1400,50),correction=c("Ripley"),nsim=99,rank=1,transform=expression(sqrt(./pi)),global=TRUE) I think I'm missing something obvious, but couldn'...

...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 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) i #<========================Doesn't display in the loop } -- Rainer M. Krug, Dipl. Phys. (Germany), MSc Conservation Biology...

Hello, I am running a Samba server (3.0.7) on a Suse 9.2 box. I have connected this server successfully to a Windows 2000 Active Directory (mixed mode). I have nsswitch.conf, krb5.conf configured and winbind seems to be running properly for the most part. With wbinfo I can get all of my user and group information. Problem is, it seems that at random times, the samba server just stops

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 d...

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 'kfun' in the ads package (this function calculates Ripley's L and confidence intervals). I have searched through help, forums, and package instructions to try...

...markcorr' calculates G(m1,m2)=m1*m2 by default. So need to specify the test function to be G(m1,m2)= sin(abs(m1-m2))^2. According to the spatstat manual (p177), I may need to 'cook up' a specific function, like this: Kdif = function(X, ..., i) { Kidot = Kdot(X, ..., i = i) K = Kest(X, ...) dif = eval.fv(Kidot - K) return(dif) } E = envelope(lansing, Kdif, i='blackoak', simulate=expression(rlabel(lansing))) So how do I tell 'envelope' that I want to specify the mark correlation test function ?? Many thanks in advance! T -------------------------...

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 Internet Service. New! Netscape Toolbar for Internet Explorer Search from anywhere on the Web...

...d 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 <- Kdot(X,...,i=i) K <- Kest(X,...) dif <- eval.fv(Kidot-K) return(dif) } E <- envelope(ppp, Kdif, nsim=100, i="Predated", simulate=expression(rlabel(ppp))) plot(E, main="clustering of predation events") I got this code from the 'Analazing spatial patterns in R Workshop notes', and it works...

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

Okay, I started over from scratch with my samba server rebuild, but I am still getting some weird issues. Here are my config files of importance: --------------/etc/samba/smb.conf-------------------- # Samba Configuration File [global] workgroup = WAYNE realm = WAYNE.LOCAL server string = Samba Server security = ADS password server =