similar to: matrix of chi-square results for all combinations of data frame

Hi Everybody I want to print a latex table containing math characters in the column heading These are the formulae I want to use as column headings. It prints OK from TeX $\sum_{i}\sum_{j}C_{P,i,j,y}\times\mathit{FC}_{i}$, $XU_{alt,y}$, $n$, $\bar{C}_{P,y}$ My plan was to create a character vector with these and later rbind the values to them. When I create the vector like:

Hi everybody I have found something (for me at least) strange with duplicated(). I will first provide a replicable example of a certain kind of behaviour that I find odd and then give a sample of unexpected results from my own data. I hope someone can help me understand this. Consider the following # this works as expected ex=sample(1:20, replace=TRUE) ex duplicated(ex) ex=sort(ex) ex

Hi Everyone, I am getting the following error message Error: cannot allocate vector of size 2.6 Gb In addition: Warning messages: 1: In dim(res$res) = dim(bi) : Reached total allocation of 8122Mb: see help(memory.size) 2: In dim(res$res) = dim(bi) : Reached total allocation of 8122Mb: see help(memory.size) 3: In dim(res$res) = dim(bi) : Reached total allocation of 8122Mb: see

Hi. I am trying to construct a svmLinear model using the "caret" package (see code below). Using the same data, without changing any setting, sometimes it constructs the model successfully, and sometimes I get an index out of bounds error. Is this unexpected behaviour? I would appreciate any insights this issue. Thanks. ~Kendric > train.y [1] S S S S R R R R R R R R R R R R R R R

Hello, I'm attempting to use the ratetable argument to survexp in the survival package. I use the example from the ?survexp help page below, and then slightly modify it to produce an error. library(survival) data(pbc) #fit a model without any factors pfit1 <- coxph(Surv(time, status > 0) ~ trt + log(bili) + log(protime) + age + platelet, data=pbc) #this works as expected

Hi, I am getting a warning message when I am fitting a generalized mixed model (mod_2) and I don't understand why because when I add just an interaction factor the model works perfectly (mod_1). Does anyone know what it happpens ? Thanks, Aïda   > mod_1<-lmer(sur15~soeviv15_4plus+frviv15_4plus+frat_15death+dad_class_new+soeviv15_4plus:dad_class_new +frviv15_4plus:dad_class_new+

Dear friends of lme, After so many year with lme, I feel ashamed that I cannot get this to work. Maybe it's a syntax problem, but possibly a lack of understanding. We have growth curves of new dental bone that can well be modeled by a linear growth curve, for two different treatments and several subjects as random parameter. By definition, newbone is zero at t=0, so I tried to force the

Dear R helpers, I have what another member on this forum described as an embarrassingly parallel problem. I am trying to fit models on subsets of some data based on unique combinations of two id factors in the dataset. Total number of combinations is 30^5, and this takes a long time. So, I would like fit models for each of the datasets produced by subsetting on the unique combinations, splitting

Hi Everybody I have started to learn how to use the XLConnect package and I think it is going to be very helpful to help me to operate between Excel users. Is there a function that can export a dataframe to a Excel sheet and automatically create a named region for every column (excluding the column heading) that correspond to the column name? If this is possible one can then also create formulae

Dear Madam or Mister, My name is Manuel Montesino and I am a PhD student at the University of Copenhagen. I am not a programmer myself, but my thesis requires the combined use of R and a model. I would be very grateful if you help me with the following issue; I am trying to combine a small piece of code written in Fortran 77 with R. The F77 code aims to select data from a library and write it

Hi all, I have made a plot with ssplot, using a SpatialPointsDataFrame. The content is quite simple, as I have 9 grid points with lon/lat coordinates and 9 values attached to these coordinates. They are in a square area of 3 by 3 gridboxes. I would like to lay a map from maps() over these values, but when I try this, the grids of the maps (smaller) do not overlap with the grids I have

I am trying to use the levelplot function from a command file. Here is the code: library(sp) library(gstat) library(lattice) gatherData <- read.table("~/gather.txt", header = TRUE) grd = makegrid(gatherData$x, gatherData$y, cell.size = 5) k <- krige(z~x+y, ~x+y, data = gatherData, newdata = grd, nmax = 5) levelplot(var1.pred~x+y, k, aspect = mapasp(k), main = "Predicted

Dear R-helpers, I get GPS readings with bug counts (bugs meaning insects in this case) made along rows in crop fields and use these to make maps of bug distribution. The GPS readings are not quite accurate enough for my purpose, so since I know what row each reading is made in, I adjust the latitudinal coordinate using: grd<-lm(lat~lon+Row,data)

Hi, Just to know if somebody had succesfully compile app_radius from http://appradius.minitelecom.org ? Here below my configuration : -> asterisk runing -> mysql running -> freeradius running -> Compiling cpprad : OK -> Compiling app_radius : not OK, here below my error message : "" make[1]: Quitte le r?pertoire `/home/grd/appradius/inc' make[1]: Entre dans le

Hi Core Team, I received an email about a problem with the help on the plotrix package. Apparently the \link tags in the help pages were showing up as literal text. I couldn't see this problem, nor any problem with the Rd files. Since the plotrix package hasn't been built for a while, I rechecked, rebuilt and reinstalled it. Sure enough, the \link tags showed up as literal text in

A larg program which worked with lme4/R about a year ago failed when I re-run it today. I reproduced the problem with the program below. -- When lme4 is not loaded, the program runs ok and fast enough -- When lme4 is loaded (but never used), the do.call fails with infinite recursion after 60 seconds. Memory used increases beyond bonds in task manager. -- I tested a few S3 based packages

A larg program which worked with lme4/R about a year ago failed when I re-run it today. I reproduced the problem with the program below. -- When lme4 is not loaded, the program runs ok and fast enough -- When lme4 is loaded (but never used), the do.call fails with infinite recursion after 60 seconds. Memory used increases beyond bonds in task manager. -- I tested a few S3 based packages

Hello R helpers, I would like to automate this code for many files of the same type. But I don´t know how to make it. In particular, i don´t know how to read many files each one as an r object with the name of the file. Then a for loop would be sufficient, right? Many thanks and a happy new year. Dominic datos <- read.table('global2001.csv',head=T,sep=';',stringsAsFactors=F)

Dear R helpers: Thanks for the previous reply. I am using Friedman racing test. According the the book "Pratical Nonprametric Statistic" by WJ Conover, after computing the statistics, he suggested to use chi-squared or F distribution to accept or reject null hypothesis. After looking into the source code, I found that R uses chi-sqaured distribution as below: PVAL <-

Dear Rs: outer(1:3, 1:3, function(df1, df2) qf(0.95, df1, df2)) I compare this F distribution results with the table, the answers were perfect. But I need to see for chi-sqaured distribution. When I employed the similar formula outer(1:3, 1:3, function(df1, df2) qchisq(0.95, df1, df2)) , I am getting unexpected results. I need to see the following values: p=0.750 ..... 1 1.323