similar to: Non-linear maximization function in R

Hello colleagues, This is a follow up to a question I posed in November regarding an analysis I was working on. Thank you to Dr. Brian Ripley and Dr. John Fox for helping me out during that time. I am conducting logistic regression on data set on psi (ESP) ganzfeld trials. The response variable is binary (correct/incorrect), with a 25% guessing base rate. Dr. Ripley suggested that I

I have hundreds of megabytes of price data time series, and perl scripts that extract it to tab delimited files (I have C++ programs that must analyse this data too, so I get Perl to extract it rather than have multiple connections to the DB). I can read the data into an R object without any problems. thedata = read.csv("K:\\Work\\SignalTest\\BP.csv", sep = "\t", header =

Hi, A simple question I hope. I wish to add a single vertical line to a plot with several density plots. Here is a simplified example. ############ thedata <- data.frame(x1=rnorm(100,1,1),x2=rnorm(100,3,1)) #create data thedata.m<-melt(thedata) densityplot(~value, thedata.m, groups=variable,auto.key=list(columns=2)) #this gives the two density plots ######### what I wish now is to add a

I am running R 2.7.0 on a Suse 9.1 linux cluster with a job scheduler dispatching jobs and openmpi-1.0.1. I have tried running one of the examples at http://ace.acadiau.ca/math/ACMMaC/Rmpi/examples.html in Rmpi and they seem to be working, except mpi.close.Rslaves() hangs. The slaves are closed, but the master doesn't finish its script. Below is the example script and the call to R. The job is

Hi, I'm testing the efficiency of the Rmpi package regarding parallelization using a cluster. I've found and tried the task pull programming method, but even if it is described as the best method, it seems to cause deadlock, anyone could help me in using this method? here is the code I've found and tried: # Initialize MPI library("Rmpi") # Notice we just say "give us

Hello r-experts, I sure could us a little help. I have an ever updating text file with timestamped data in it. I can reformat in anyway I want if need be but currently I have chosen to make columns of date, time and measuresed value (comma delimeted and with the dates and times in quotes to interpret them as strings). Here is a small section of my text data file:

The problem: I would like to translate the Octave algorithm in griddata.m to R. Within the griddata algorithm calls are made to the Delaunay function. For the R translation I have found delaunayn within the "geometry" package and also the deldir package. Both do similar things but give slightly different results depending on the input. The question is, what is making the results for the

"The question is, what is making the results for the R packages different from each other?" There are literally thousands of R packages, contributed independently by thousands of people. There should be no expectation of consistency or for that matter, "correctness", among them. Caveat emptor. Only within the base R distribution, maintained and mostly written by the R Core

I am trying to plot multiple densityplots on each panel, and using panel.groups to do some additional plotting (not included in the example) as in this example. library(lattice) thedata <- data.frame(x=rnorm(1200),class=rep(1:3,each=200,times=2), group=rep(1:2,each=100,times=6)) densityplot(~x | class,groups=group, xlab='x', panel.groups =

I have the attached class that I''m writing. The problem that I''m running into is that I can not access the options from the createArray function which get called after the ajax request gets done. I want to move the values of the xml file to an array and story it in the options variable. Can someone explain what I''m doing wrong? var LeaderInfo = Class.create();

Dear all, how can I, with R, transform a presence-absence (0/1) matrix of species occurrences into a presence-only table (3 columns) with the names of the species (1st column), the lat information of the sites (2nd column) and the lon information of the sites (3rd column), as given in the below example? Thanks a lot for your help! Christian my dataframe: site lat lon spec1 spec2 spec3 spec4

This is probably buried somewhere in the R help archives, but I've been unable to find it, so perhaps the keywords I use here will help bring the topic to the surface more easily for future users. I want to write my own modeling function (ultimately for some multidimensional windowing - but this question is on scripting basics). For purposes of figuring out my needs, lets just consider

Dear all, maybe somebody can provide some help for this problem: Example: I've got the following dataframe "data": grid.id<-c(1:4) lat<-c(10,12,13,15) species1<-c(0,0,0,1) species2<-c(1,1,0,0) species3<-c(1,1,1,1) data<-data.frame(cbind(grid.id,lat,species1,species2,species3)) How can I, out of "data" make a new dataframe, where the cells of value

Dear R users, I am using the MICE package. Specifically, at some point in my code I have imp2=mice(PoptotalMICE,imputationMethod="logreg2") And R returns... iter imp variable 1 1 MICEYError in logitreg(xobs, yobs, intercept=F) : couldn't find function "ms" I have been looking for this ms function on the web, hoping it was just a matter of downloading a

Hello, I have a data frame with 1425 observations, 539 of which are zeros. I am trying to fit the following ZINB: f3<-formula(Nbr_Abs~ Zone * Year + Source) ZINB2<-zeroinfl(f3, dist="negbin", link= "logit", data=TheData, offset=log(trans.area), trace=TRUE) Zone is a factor with 4 levels, Year a factor with 27 levels, and Source a factor with 3 levels. Nbr_Abs is counts

Hi, I want to analyse a contigency table (3 x 12) with a fisher.test beacause there are cells that are less than 5. ?mmen Anken Baf Belchen H?chi Hof Porti R?m Schmutz Sch?n Sissa Tann class14 7 26 150 2 46 68 126 66 3 31 7 61 class24 7 6 55 5 49 71 93 90 1 18 16 79 class34 1 1 4 3 19 8 29 61

Dear all, how can I, with R, transform a presence-only table (with the names of the species (1st column), the lat information of the sites (2nd column) and the lon information of the sites (3rd column)) into a presence-absence (0/1) matrix of species occurrences across sites, as given in the below example? Thanks a lot for your help! Christian My initial table: species lat lon sp1 10 10

Hi there, In multiple regression one way to view R^2 is as (the square of) the correlation between original y's and the estimated y's. Suppose you fit a multilevel model with random intercept for each cluster. Would it be valid to compute an R^2 by using fixed effects plus the group intercepts to reduce the residuals? I suspect this has been done and, given its absence from the lmer

Dear all, I would like to use the residuals in a general linear mixed effect model to diagnose model fit. I know that the resid function has been implemented for linear mixed models but not yet for general linear mixed effects. Is there a way to get them out of lmer fit objects? I tried searching the r-help archive and found nothing. I tried and failed to replicate what (I guessed would be

Dear R-forum, I am looking for a good resource/help on working with POSIXct values and controlling the pretty x-axis labels and tick marks for a data VS time plots. Specifically, I wish to do programming logic which creates different vertical ablines calculations based on the range of times which i am working on. The default plot results are adequate, but I would love to make explicit calls on