similar to: finding "clusters" in 2-dimensional data

Dear all! Although the Psycho-Toolbox for Matlab is free software, Matlab isn't. I'm planning to do an experiment where it's essentail to travel to the subjects, not let the subjects come to where the Matlab licences are :-( So I need to use a free software for my experiment if I don't want to by an extra Matlab licence (which I don't want to). Did anyone ever try to do

HI: I need ideas on how to make this code shorter (maybe with a second loop?). The code as it is works, but in this case I only have 14 samples, but it will become insane with more, so I need a way to make it more automatic. The problem is that the output from ts1, ts2, and so on is a vector with more than one value, so I do not know how to solve this. Thanks Prenewbie The code is the

Hello - I am having trouble extracting data from NetCDF data files using RNetCDF. The data files each have 3 dimensions (longitude, latitude, and a date) and 3 variables (latitude, longitude, and a climate variable). Here is some of the output from print.nc for clarity: ----- dimensions: month = UNLIMITED ; // (1368 currently) lat = 3105 ; lon = 7025 ; variables: float

> From: Jean-Louis Abitbol > > Dear All, > > I would like to merge a data frame such as: > > > basetab > subject dose cmax > 1 1031 50 21.8 > .... > > with the result of a by processing such as: > > > tmax<-by(pkga,subject,f.tmax) > > tmax > subject: 1031 > [1] 6 > --------------------------------------------------

I have a set of time-series climate data with missing entries. I need to add rows for these missing entries to this data set. The only way I know to do this is unsing a foreloop, but this won't work on a list. I've tried to convert the list to a data frame, but that won't happen, either. I want to fill rows in this table: > newtest[10:15,] yrmos yearmo snow.sum snow.mean

Forgive my poor English. There is Tmax Window, the 1st windows XP compatible proprietary OS from Korea. Tmax company showed screenshot of Tmax Windows. But it is known as they mixed images with real XP and OpenOffice suite screenshots. http://mr-dust.pe.kr/entry/Tmaxwindow-screenshot-failed Tmax Window is doubtful about stolen ReactOS source code: This is a post of a tmax developer.

Hi, I have R 2.6.0 with updated lme4 and Matrix packages, and I am trying to fit a nonlinear multilevel model. I get the following error message: Error in nlmer(f ~ grModel(x, w, Tmin, Tmax, Topt, kopt, m) ~ kopt | flat, : gradient attribute of evaluated model must be a numeric matrix and I wonder what this may indicate. The nonlinear model I try to fit is as follows: > grModel

I'm trying to understand what goes on in the process that nls() uses. This converges without much drama: > rate.nls <- nls(Dev ~ exp(rho * (T)) - exp(rho*Tmax - (Tmax - T)/del)+ + lam , data = xx, trace = TRUE, + start = c(rho = 0.15, del = 7, lam = .02, Tmax = 30)) 599.7841 : 0.15 7.00 0.02 30.00 4.69849 : 0.14673457 6.83443060 -0.01417782

Hi all, I have a strange problem and rigth now I can't figure out a solution. Trying to calculate an ANOVA with one between subject factor (group) and one within (hemisphere). My dependent variable is source localization (data). My N = 25. My data.frame looks like this: > ML.dist.stack subj group hemisphere data 1 1 tin left 0.7460840 2 2 tin left

Hi all! I have written some code in C for simulating the fate of population using a dll loaded in R. During this simulation the population may go extinct such that the length of its trajectory is unknown beforehand. I wonder there is a way to define the size of the result in C and make it known to R to get the vector appropriately. I have defined the output size very much larger than

Dear list, I was trying to use the R API for optimization method "Simulated annealing" void samin(int n, double *x, double *Fmin, optimfn fn, int maxit, int tmax, double temp, int trace, void *ex); but I encountered the following problem: The implementation of the function samin (as seen in src/main/optim.c) passes its void * argument "ex" into the function

Hello, I am an R newbie, trying to use lsoda to solve standard Lotka-Volterra competition equations. My question is: how do I pass a parameter that varies with time, like say, phix <- 0.7 + runif(tmax) in the example below. # defining function lotvol <- function(t,n,p){ x <- n[1]; y <- n[2] rx <- p["rx"]; ry <- p["ry"] Kx <-

I am trying to run the following code in R on a Linux cluster. I would like to use the full processing power (specifying cores/nodes/memory). The code essentially runs predictions based on a GAM regression and saves the results as a CSV file for multiple sets of data (here I only show two). Is it possible to run this code using HPC packages such as Rmpi/snow/doParallel? Thank you!

Dear all Im new in R I have a necdf data set that I want to plot : this is my data set [1] "file Tmax.DJF.daily.1981_1999.echama2.nc has 4 dimensions:" [1] "longitude Size: 127" [1] "latitude Size: 110" [1] "ht Size: 1" [1] "t Size: 1680" [1] "------------------------" [1] "file Tmax.DJF.daily.1981_1999.echama2.nc has 1

Very much a rookie at R, and have only recently started using it again so pardon the simple question. I am trying to produce a box plot from one data set and then overlay a line plot from another data set. The box plot data set is made up of 20 sets of 30 data points, or 600 total data points. The line has only 30 total data points. The box plot is plotting fine, but for some reason, the line plot

Hi everyone, I'm a newbie to R and to linear mixed effects modeling, so please have mercy :-) Just wanted to check, whether what I'm doing is alright. I've collected data concerning tonotopic organization of the auditory cortex in humans, and I have approximately 1400-1800 data/time points per person (13 in total). Observations were made how the focus of neuronal activity changed

Hi all, I am trying to run an autologistic model using the function errorsarlm from spdep package. **I built an XY matrix extracting the two colums from matriz** coords1<-matriz[matriz$casos1==1, c(4,5)] coords1<-as.matrix(coords1) **I identify neighbours of region points** nb20<-dnearneigh(coords1,0,20,longlat=TRUE) ** I build a neighbours list with spatial weights**

Hello everyone, I am working for a few days already on a basic algorithm, very common in applied agronomy, that aims to determine the degree-days necessary for a given individual to reach a given growth stade. The algorithm (and context) is explained here: http://www.oardc.ohio-state.edu/gdd/glossary.htm , and so I implemented my function in R as follows: DD <- function(Tmin, Tmax, Tseuil,

Dear all, I am trying to create a vector name, for example tmax.195012 from tmax., 1950 and 12. Obviously I don't wish to simply type it because the 3 name components are changing in each iteration within a loop. Is there any way of concatenating those 3 components (which are a mixture of numbers and letters)? Thanks for reading, Panos

I've got an rsync job which is consistently failing, but I've been unable to diagnose the problem. FAQ/Google/docs/etc. checked and no luck. Basically, it looks like the rsync process invoked on the far end is exiting, and then the local process waits until the timeout and exits. Both systems are Sun boxes, Ultra 10 or better with 256+ MB of memory. Rsync version is 2.5.0 on the local