similar to: Multi part problem...array manipulation and sampling

Hi, I would like to use the multinomRob function to test election results. However, depending on which independent variables I include and how many categories I have in the dependent variable, the model cannot be estimated. My data look like this (there are 68 observations): > head(database) RESTE09 GAUCHE09 PDC09 PLR09 UDC09 MCG09 RESTE05 GAUCHE05 PDC05 D1 1455

Dear R listers, I am trying to create a new variable that uniquely identifies groups of observations in a dataset. So far I couldn't figure out how to do this in R. In Stata I would simply type: egen newvar = group(dim1, dim2, dim3) Please, find below a quick example to show what I am dealing with: I have a dataset with 4 variables: var <- runif(50) ## a variable that I want to group

Dear R-help community, I am working with multidimensional contingency tables and I am having trouble getting loglm to run on all dimensions without typing out each dimension. I have generated random data and provided output for the results I want below: d1.c1 <- rnorm(20, .10, .02) d1.c2 <- rnorm(20, .10, .02) d2.c1 <- rnorm(20, .09, .02) d2.c2 <- rnorm(20, .09, .02) d3.c1 <-

Hello all, I have been using the function ordirgl to plot 3D dynamic ordinations. The ordirgl function works just fine. IN fact, I was even able to write a function that allows me to identify points in the 3D plot: identify.rgl<-function(env_var,ord,dim1,dim2,dim3) { tmp<-select3d(button="left") tmp.keep<-tmp(ord[,dim1],ord[,dim2],ord[,dim3])

Hi, See my example below. a<-array(1:12,c(2,3,2)) > a , , 1 [,1] [,2] [,3] [1,] 1 3 5 [2,] 2 4 6 , , 2 [,1] [,2] [,3] [1,] 7 9 11 [2,] 8 10 12 I want to get a result something like dim1 dim2 dim3 elements 1 1 1 1 2 1 1 3 2 2 1 2 I tried the data.frame and expand.grid functions,

High! How can I add variable labels (rownames for instance) to a plot created with ‚clouds’ ( clouds(dim3~dim1*dim2)) – package lattice? Thanks in advance! Martina Renninger [[alternative HTML version deleted]]

Full_Name: Manuel L?pez-Ib??ez Version: R version 2.6.2 (2008-02-08) OS: linux-gnu Submission from: (NULL) (164.15.10.156) This is only relevant for CPU intensive child processes. Otherwise, the problem is not obvious. Therefore, we need a CPU intensive program like this one: /************************************/ /*** Compile with: gcc -o timer-test -O0 timer-test.c -lm */ #include

I am trying to multiply a 3D array of 4x4x4 by the 4 3D arrays of a 4D array with dimensions 4x4x4x4 (the last dimension being the one that I want to split by). (4x4x4 array) > hiaAry , , a1 i1 i2 i3 i4 h1 9.5936098 6.001040 0.08772 0.3138600 h2 1.2003500 1.454570 2.79248 0.0000000 h3 0.1346500 0.201220 0.39256 0.5464000 h4 0.0109000 0.012270 0.16417 0.2766900 ,

libswfdec-gtk/swfdec_gtk_widget.c | 4 +- libswfdec/jpeg/jpeg.c | 55 ++++++++++++++++++++++---------------- libswfdec/jpeg/jpeg_rgb_decoder.c | 1 libswfdec/swfdec_image.c | 46 +++++++------------------------ 4 files changed, 47 insertions(+), 59 deletions(-) New commits: diff-tree a171b4ba49fbd8fa8addb521184fc9b2cde60e50 (from

Dear colleague, I not sure this R code is correctly ? I would to show the number of Sample Size at Sample Size Axis that line draw from Power Axis (80%) from R code. How I show this and select the most appropriate of this power (.79955687 - 80983575). Thank for your help and answer. Best Regards, Nikom Thanomsieng, Email: nikom at kku.ac.th .... #Power analysis: Sample size for

Hi there, Could somebody help me disect this legacy R script I inherited at work, I have two questions: 1. I've tried to upgrade our R version from 1.6.2 (yeah, I know), to R 2.0, but some of the lines in this script are not compatible with R 2.0, could someone help me figure out where the problem is? 2. the jpeg generated (attached) seems to be off on some of the data, is there a better way

Below is code that introduces a list comprehension syntax into R, allowing expressions like: > .[ sin(x) ~ x <- (0:11)/11 ] [1] 0.00000000 0.09078392 0.18081808 0.26935891 0.35567516 0.43905397 [7] 0.51880673 0.59427479 0.66483486 0.72990422 0.78894546 0.84147098 > .[ .[x*y ~ x <- 0:3] ~ y <- 0:4] [,1] [,2] [,3] [,4] [,5] [1,] 0 0 0 0 0 [2,] 0 1 2

[[this bounced first, because it has 'help' in the Subject line ... -- Martin Maechler ]] I am a complete novice R programmer. (Though I know C quite well) I am trying to write some R code to do the following simulation. There is a 2-frame "movie" of noise and signal dots. the noise dots have random positions in each frame. The signal dots are placed randomly in frame 1,

Dear all, I had to extracts/set elements from/in a matrix. Let say I have two vectors dim1 and dim2 of indices in the respective two dimensions of a matrix: I want to extract all the corresponding elements. I the case of a nxn matrix, dim1 <- 1:n and dim2 <- 1:n would extract the diagonal. I know one way would be to use the functions 'row' and 'col', but the matrixes I

Dear R users, I'am using marray and Limma packages to analyze genepix output. 1) how can I filter bad spots from my data (data contains 3 types of bad spots). my experiment contains 12 samples and the bad spot are not associated to the same probes 2) how can I remove control probes from my data ? I'm sorry, i'm new with R and I can't find answer in packages doc. best regards,

From: Andreas Rammhold <andreas at rammhold.de> With OpenSSL versions 1.0.2r & 1.1.1b there were changes in regards to how OpenSSL treats misuse of Encrypt/Decrypt EVP methods in the opposite case. E.g. using the encrypt methods in a decrypt context. OpenSSL now returns an error in these situations. [1] Since tinc used the EVP_EncryptUpdate function in the cipher_decrypt function the

I noticed this in current intermediate patch version: > runif(0,0,4095) numeric(0) > round(runif(0,0,4095)) [1] NA I don't like it, but maybe it is the way it is supposed to be. I would prefer for it to stay numeric(0). I notice also > ceiling(runif(0,0,4095)) numeric(0) > floor(runif(0,0,4095)) numeric(0) which leads me to thing round() is not working right. I have some code

Hi R helpers, I'm trying to fit a rather complex model to some simulated data using lme and am not getting the correct results. It seems there might be some identifiability issues that could possibly be dealt with by specifying starting parameters - but I can't see how to do this. I'm comparing results from R to those got when using GenStat... The raw data are available on the

  Hello All,   I am working with dlm for the purpose of estimating and forecasting with a Kalman filter model. I have succesfully set up the model and started generating results. Of course, I need to somehow be sure that the results make sense. Without any apparent target to compare with, my natural selection is the results by odinary least square. The idea being that if I choose a diffuse prior,

Hi all, I am using c++ functions in R by Rcpp and inline packages. The code is quite simple, but the R session always automatically crash after some running time. Does anyone here familiar with Rcpp and inline? What¡¯s the problem in the following code? I have checked the input values, no NA and other strange value exists. Thank you for your attention! > mkc <- cxxfunction(