similar to: Creating an array [0 to 101] of a list

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() }

Can anyone explain what I'm missing here? max(pp1 <- package_version(c("0.99999911.3","1.0.4","1.0.5"))) ## [1] ?1.0.4? max(pp2 <- package_version(c("1.0.3","1.0.4","1.0.5"))) ## [1] ?1.0.5? I've looked at ?package_version , to no avail. Since max() goes to .Primitive("max") I'm having trouble figuring out

Hello. I have n files in a directory: file1, ..., filen. I read them with the following commands: list=scan(file="list",what=list(nom="")) # in the file list, I have all the filenames. n=length(list[[1]]) for (i in 1:n){ aux <- paste("p",i,sep="") assign(aux, as.matrix(read.table(list[[1]][i]))) } R creates the matrices p1,p2,...,pn. I want

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 I have two processes which take with a certain probability (p1 and p2) x number of years to complete (age1 and age2). As soon as thge first process is completed, the second one begins. I want to calculate the time it takes for the both processes to be completed. I have the following script which gives me the answer, butI think there must be a more elegant way of doing the calculations

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, 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

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 everyone, ? I am trying to do a horizonplot using my own time series data. I know that there is a horizonplot function in latticeExtra, but on closer examination i think that the graph itself is slightly wrong (it displays some regions as triangles and i think they should be trapezoids, and the red regions (that are below the baseline) are displayed on top of the blue areas ? while i think

Hi I use the following code and it stores the results of density() in the list dr: dens <- function(run) { density( positions$X[positions$run==run], bw=3, cut=-2 ) } dr <- lapply(1:5, dens) but the results are stored in dr[[i]] and not dr[i], i.e. plot(dr[[1]]) works, but plot([1]) doesn't. Is there any way that I can store them in dr[i]? Thanks a lot, Rainer -- Rainer M. Krug,

I have a data frame (attached) that has interpolated EOT errors for each minute before flight landing. It also has the runway and an index for the flight: > > times[1:4,] time error runway flight 1 0 -0.02206235 04R 1 2 1 -0.07961631 04R 1 3 2 -0.13795380 04R 1 4 3 -0.20726073 04R 1 > > sapply(times, class) time error

I'm trying to obtain numerical derivative of a probability computed with mvtnorm with respect to its parameters using grad() and jacobian() from NumDeriv. To simplify the matter, here is an example: PP1 <- function(p){ thetac <- p thetae <- 0.323340333 thetab <- -0.280970036 thetao <- 0.770768082 ssigma <- diag(4) ssigma[1,2] <- 0.229502120

Dear all, I'm looking for primary help at aggregating table() results and at writing a loop (if useful) My dataset ( http://goo.gl/gEPKW ) is composed of 23k rows, each one representing a point in the space of which we know the land cover over 10 years (column y01 to y10). I need to analyse it with a temporal sliding window of 5 years (y01 to y05, y02 to y06 and so forth) For each period

Hi if I try to import a raster layer which consists only of NULL values from grass by using the readRAST6, I get an error message: > readRAST6("HSericea_seedsDisperse_2007") ERROR: Invalid value for null (integers only) Error in readBinGrid(rtmpfl11, colname = vname[i], proj4string = p4, integer = to_int) : no such file:

Hi R, I have a list > class(pp2) [1] "list" > length(pp2) [1] 1244 It is in the below format RIC Trade.Date Close.Price Currency.Code Convertion.Rate New.Price ABCD.SZ 2008/02/29 15.30 CNY 0.1408 2.154240 ABCD.SZ 2008/01/31 15.27 CNY 0.1392 2.125584 ABCD.SZ 2007/12/31 14.88 CNY 0.1371 2.040048

Rainer M Krug writes: > Thorsten Wiegand used in his paper Wiegand T., and K. A. Moloney 2004. > Rings, circles and null-models for point pattern analysis in ecology. > Oikos 104: 209-229 a statistic he called O-Ring statistic which is > similar to Ripley's K, only that it uses rings instead of circles. > > http://www.oesa.ufz.de/towi/towi_programita.html#ring

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 table called npl containing results of simulations. It contains about 19000 entries and the structure looks like this: NoPlants sim run year DensPlants 1 6 lng_cs99_renosterbos 1 4 0.00192 . . . it has 43 different entries for sim and year goes from 1 to 100, and run from 1 to 5. I would like to calculate the mean of DensPlants for each

I am using ggplot2 to make a boxplot that overlays a scatterplot: pp = qplot(time, error, data=times, size=I(1), geom="jitter", main=title, ylab="Error (min)", xlab="Time before ON (min)", alpha=I(1/10), color=times$runway, ylim=c(-30,40)) pp2 = pp + with(times, facet_wrap(~ runway, ncol=2)) print(pp2 + geom_boxplot(alpha=.5,