similar to: reason for error in small function?

Hello, I am trying to conduct a bi-variate ripley's k using the k12hat function in the splancs package (found here http://rss.acs.unt.edu/Rdoc/library/splancs/html/k12hat.html). Although, I receive an error when getting to the bboxx part of the code: poly <- list(x=c(fire4$X, nar4$X), y=c(fire4$Y, nar4$Y)) plot(seq(5,80,5), sqrt(k12hat(fire4), as.points(nar4),

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

Dear forum, I would like to use the kernel2d or spkernel2d in the Splancs-package, but it does not recognize my polygon data. "Error in kernel2d(as.points(ptsbin), polygonprov, h0 = 2, nx = 100, : " is the error message. Invalid poly argument The data are defined as follows: polgonprov<-list(x=polyprov$X, y=polyprov$Y) with X and Y coordinates in the Lambert1972

Dear all, Does anyone have any idea on how to speed up the for() loop below. Currently it takes approximately 2 minutes and 30 seconds. Because of the size of Nsim and N, simulating a multivariate normal (instead of simulating Nsim times a vector of N normal distributions) would require too much memory space. Many thanks for your kind help, Simona N=3000 PD=runif(N,0,1) cutoff.=qnorm(PD)

Dear all, I had to place points at random, one in each of larger number of polygons (actually in objects of class 'SpatialPolygonsDataFrame' , see sp library), and tried first to do it using spsample (from sp). Surprisingly, every 5-15 trials, the output was a NULL value. The doc says that ' this may occur when trying to hit a small and awkwardly shaped polygon in a large

Howdy Gurus I am try to compute envelope of Khat from simulations of complete spatial randomness using R package of "Splancs." I got the following error: > UL.khat <- Kenv.csr(length(X_coord), bnd, nsim=100, s) Doing simulation 1 Error in runif(n, min, max) : invalid arguments In addition: Warning message: NAs introduced by coercion I think that I have a problem with

Dear All, In the moment i'm using the map and maptools package to read shapefiles and display the maps. I'm looking for the possibility to draw points (randomly positioned or positioned according to a grid) into the polygons instead of filling the polygons with colors. For example: a map (shapefile) with 10 countries, 15 points in the polygon of country A, 20 points in the

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, I have a problem that concerns combination of the package Maptools and Splancs I have 2 shapefiles that i want to manipulate (one of type point and one polygon).I import them in R using Maptools but then i can't estimate a quartic Kernel using Splancs. The package doesn't recognize the shapes (invalid points and poly argument).I don't know if this is an easy task but i have

Dear all, I have just sent an email with my problem, but I think no one can see the red part, beacuse it is black. So, i am writing again the codes: rm(list=ls()) #remove almost everything in the memory set.seed(180185) nsim <- 10 mresultx <- matrix(-99, nrow=1000, ncol=nsim) mresultb <- matrix(-99, nrow=1000, ncol=nsim) N <- 200 I <- 5 taus <- c(0.480:0.520) h <-

Dear all, I am trying to run a loop in my codes, but the software returns an error: "subscript out of bounds" I dont understand exactly why this is happenning. My codes are the following: rm(list=ls()) #remove almost everything in the memory set.seed(180185) nsim <- 10 mresultx <- matrix(-99, nrow=1000, ncol=nsim) mresultb <- matrix(-99, nrow=1000, ncol=nsim) N

I?m working on an R-implementation of the simulation-based finite-sample null-distribution of (R)LR-Test in Mixed Models (i.e. testing for Var(RandomEffect)=0) derived by C. M. Crainiceanu and D. Ruppert. I'm in the beginning stages of this project and while comparing quick and dirty grid-search-methods and more exact optim()/optimize()-based methods to find the maximum of a part of the

Dear all, I am a new user in r and I am facing some problems with the quantile regression specification. I have two matrix (mresultb and mresultx) with nrow=1000 and ncol=nsim, where I specify (let's say) nsim=10. Hence, the columns in my matrix represents each simulation of a determined variable. I need to regress each column of mresultb on mresultx. My codes are the following:

## Package Needed library(fields) ## Assumptions set.seed(123) nsim<-5 p<-2 ## Generate Random Matrix G G <- matrix(runif(p*nsim),nsim,p) ## Set Empty Matraces dmax and dmin dmax<- matrix(data=NA,nrow=nsim,ncol=p) dmin<- matrix(data=NA,nrow=nsim,ncol=p) ## Loop to Fill dmax and dmin for(i in 1:nsim) { dmax[i]<- max(rdist(G[i,,drop=FALSE],G)) dmin[i]<-

Craig, Thanks for your follow-up note on using the asypow package. My problem was not only constructing the "constraints" vector but, for my particular situation (Poisson regression, two groups, sample sizes of (1081,3180), I get very different results using asypow package compared to my other (home grown) approaches. library(asypow) pois.mean<-c(0.0065,0.0003) info.pois <-

Dear list, After running for a while, it crashes and gives the following error message: can anybody suggest how to deal with this? Error in if (ratio0[i] < log(runif(1))) { : missing value where TRUE/FALSE needed ################### original program ######## p2 <- function (Nsim=1000){ x<- c(0.301,0,-0.301,-0.602,-0.903,-1.208, -1.309,-1.807,-2.108,-2.71) # logdose

Hi R-users, I have a problem for updating the estimates of correlation coefficient in simulation loop. I want to get the matrix of correlation coefficients (matrix, name: est) from geese by using loop(500 times) . I used following code to update, nsim<-500 est<-matrix(ncol=2, nrow=nsim) for(i in 1:nsim){ fit <- geese(x ~ trt, id=subject, data=data_gee, family=binomial,

All: Are there any functions out there for selecting all the points in a region of a plot. I envision something like the identify() function except one could circle a cloud of points (and perhaps a vector would be returned of the same length as the points plotted indicating logical membership in the circled cloud). Perhaps someone has done something with the locator() function that would

I am trying to generate two dimensional random coordinates. For randomly distributed data I have simply used >xy<-cbind(runif(100),runif(100)) However I also want to generate coordinates that are more uniformly distributed, and coordinates that are more contagiously distributed than the above. Can anyone make any suggestions Thanks. Dr Terry Beutel Rangeland Scientist Animal

Hi, I am running simulations that does multiple comparisons to control. For each simulation, I need to model 7 nls functions. I loop over 7 to do the nls using try if try fails, I break out of that loop, and go to next simulation. I get warnings on nls failures, but the simulation continues to run, except when the internal call (internal to nls) of the chol2inv fails.