similar to: minimisation problem, two setups (nonlinear with equality constraints/linear programming with mixed constraints)

Hi everybody, I'm working on Mac OS X and R-2.1.0 (by the way, sorry for the multiple emails last time, had a technical problem, and thanks for the constructive comments.) I have a .R function which calls a .C function. The R function's name is K_MEANSR.R and the other is K_MEANSC.C. I compile it with 'R CMD SHLIB K_MEANSC.C' in the terminal. I get both .so and .o files.

Hi all, I am wandering.. is it possible to cluster data which is in a single column ? for example.. I have some data as follows: 4013 7362 7585 9304 11879 14785 21795 30500 30669 30924 33988 36975 40422 42911 50501 51593 53729 54338 55497 57337 61993 62601 66229 69815 69933 70760 71340 75921 83972 90134 91061 . . . is it possible to cluster this data since it is in a single column ? I have

This code works: x<-letters[1:6] ycols<-23:28 xcols<-rep(c(3,4,5,8),each=length(ycols)) somertime<-function(i,j)somers2(Pred_pres_a_indpdt[,i,,], population[,j]) results<-mapply(somertime,xcols,ycols) How can I make variable "h" work? x<-letters[1:6] ycols<-23:28 xcols<-rep(c(3,4,5,8),each=length(ycols))

Hi Apart from nlm() with the stepmax= argument, is there any other >1 dimensional minimisation function where I can limit the step size dynamically. With the NAG routine E04NBF (I think) I used to bound the size of the next step using a*arctan(x/a) tricks where a function was particularly difficult near a boundary and thus 'steer' the result within legal limits. The function I am

Dear R users, I am searching for a general minimisaton function like 'ms' in R. Please give me a hint! -- ------------------------------------------------------------ Dipl. Inform. J. Hedderich Institut f?r Medizinische Informatik und Statistik im Klinikum an der CAU Phone : 0431/5973182 Brunswiker Str. 10

Hi there, I have a multiple for loop over a list of data frames for ( i in 1:(N-1) ) { for ( j in (i+1):N ) { for ( p in 1:M ) { v_i[p] = alist[[p]][i,"v"] v_j[p] = alist[[p]][j,"v"] } rho_s = cor(v_i, v_j, method = "spearman") rho_p = cor(v_i, v_j, method = "pearson"

Hi, It is my understanding that the eigenvectors of a circulant matrix are given as follows: 1,omega,omega^2,....,omega^{p-1} where the matrix has dimension given by p x p and omega is one of p complex roots of unity. (See Bellman for an excellent discussion on this). The matrix created by the attached row and obtained using the following commands indicates no imaginary parts for the

I am trying to use lme to fit a mixed effects model to get the same results as when using the following SAS code: proc mixed; class refseqid probeid probeno end; model expression=end logpgc / ddfm=satterth; random probeno probeid / subject=refseqid type=cs; lsmeans end / diff cl; run; There are 3 genes (refseqid) which is the large grouping factor, with 2 probeids nested within each refseqid,

Dear R-Users, I have the following problem: I would like to create a postscript file containing an r-plot with the string "\\vartheta" in it (reason: this is later converted to the TeX-string "\vartheta" and a vartheta is printed in the figure). In the minimal example below, the problem is that the created postscript file does _not_ contain the string "\\vartheta

Hey guys, sorry for the inconvenience (this might be a hundred times answered question), but I have been searching a while and gave up about the following: I have the following, table and data: table <- seq(255, 0, by=-1) data <- c(1,8,...) <--- doesn't matter what's in here Which would be the most efficient way to replace each data value, v_i, by table[v_i + 1] ? And, maybe

I am trying to use lme to fit a mixed effects model to get the same results as when using the following SAS code: proc mixed; class refseqid probeid probeno end; model expression=end logpgc / ddfm=satterth; random probeno probeid / subject=refseqid type=cs; lsmeans end / diff cl; run; There are 3 genes (refseqid) which is the large grouping factor, with 2 probeids nested within each refseqid,

A question about: Kalman in R, time series and deJong-Penzer statistic - how to compute it using available artefacts of KalmanXXXXX? Background. in the paper http://www.lse.ac.uk/collections/statistics/documents/researchreport34.pdf 'Diagnosing Shocks in TIme Series', de Jong and Penzer construct a statistic (tau) which can be used to locate potential shocks. [p15, Theorem 6.1 and

Hello all, Is there a way in R to compute the multivariate normal density of every pair of entries in a vector efficiently instead of using for loop? For example Suppose I have a vector a=c(v_1,...,v_p)=c(0.5343909, -0.7784353, -0.0568370, 1.8772838, -1.3183407, 0.8227418,...) I want to compute density(v_i, v_j) for every pair of entries (i,j) (i!=j) in a. The joint bivariate distribution

Hi. If I have a vector, v_1, and another vector of positive integers, i_1, the same length as v_1, then rep(v_1,i_1) will repeat v_i[j] exactly i_1[j] times, like so: >rep(c(1,2,3),c(3,2,1)) [1] 1 1 1 2 2 3 > I'd like to do the same sort of thing where I replace v_1 with a matrix, and the jth row of the matrix is repeated i_1 times. Obviously, I could do this with for loops, like

scaling<-4 xywidth<-480 resolution<-150 png(filename = "c:/r/anschluss/plots/4.png", width = xywidth*scaling, height = xywidth*scaling,pointsize = 12, bg = "white", res = resolution*scaling) ...... barplot(xrow,col = barcolors,cex.axis=scaling, ylab="mean time till attachment in sec",cex.lab=1.2*scaling) I tried to scale the barplot but there is one

Hi all, I'm trying to use the package read.table within a foreach loop. I'm grabbing 500M rows of data at a time from two different files and then doing an aggregate/tapply like function in read.table after that. I had planned on doing a foreach loop 39 times at once for the 39 files I have, but obviously that won't work until I figure out why the segfault is occurring. The

Hi, I need to find the minimum value of the parameter, s, such that the function f(s,t) > 0 (where -Inf < t < Inf) I've looked into optim, constrOptim and others but they don't seem to do this. Des anyone have some suggestions? Thanks in advance. [[alternative HTML version deleted]]

Look at it, and you'll see the black outline is missing on the right side of the minimise button. This has been bugging me for a while. I've attached a zoomed in shot, so you can see easily what I mean. It's not a bug in the theme, but in gtk-window-decorator's Metacity theme support, as the border displays perfectly in Metacity. Does it happen with other themes? --------------

Hi all, Is it possible to programmatically minimise the main window of the windows R gui? I'm designing a small gui with gwidgets & RGtk2 for an non-statistician to use, and it would be nice if I could easily hide all the R stuff that they don't need. Thanks, Hadley -- http://had.co.nz/

I have installed Simple Sudoku (http://www.angusj.com/sudoku/index.php) but I cannot minimise it, nor go to another screen to do something else. If I try, its window gets larger, vertically. I am using wine 20050725 (which is what is packaged for my system at present), on a Debian system running XFree86, with icewm-gnome. Can anyone advise why this program "hogs attention"? -- Phil