search for: dim2

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 dim1 <- factor(rep(1:3, length.out= 50), labels = c("x","y","z") ) ## 3 variables that should form...

...218897 0.05659316 D4 2182 9208 7288 10654 2951 5205 0.08227831 0.2591124 0.19605699 D5 6129 13909 12691 15560 3129 12551 0.10438878 0.2362780 0.23772964 D6 3027 13517 4702 17899 5299 5758 0.10507522 0.2034102 0.07564233 PLR05 UDC05 MCG05 dim1 dim2 dim3 D1 0.3006495 0.08555836 0.12254194 0.4327918 -0.37563170 0.23139759 D2 0.4879385 0.09903729 0.05058832 1.2723817 0.03128996 -0.10629471 D3 0.2296300 0.07822276 0.12785602 -0.8002237 -0.12194377 0.18147181 D4 0.3051325 0.06789533 0.08952449 0.4321835 0.11445829 0.24636903 D5 0.28...

Hi, I am trying to infer the dimension of an opened bitmap (png, jpeg, bitmap device...) from par() parmeters. From the help on par(), I found that: > dim <- c(400, 200) > png("foo.png", width=dim[1], height=dim[2]) > dim2 <- par("din") * par("cra") / par("cin") > dev.off() > dim2 [1] 399.9999 199.9999 I've tried the above on Rv2.4.1 on WinXP and Linux with png() and jpeg() and the precision is good enough. However, when I turn to the bitmap() device, I found the following...

...nclude <stdio.h> #include <stdlib.h> #include <math.h> double alpha, beta; int size = 1000; #define WORK_create_matrix(TYPEOFMATRIX) \ \ TYPEOFMATRIX ** m_create_##TYPEOFMATRIX##_matrix ( \ int dim1, int dim2, int line, const char*file) \ { \ TYPEOFMATRIX **p; \ int i; \ \ p = malloc (sizeof(TYPEO...

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, but the results are not what i want. I think there must be an easy method to do it. Anybody can tell me that function or method? Thanks. ... --...

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 have...

...lt;- rnorm(20, .09, .02) d2.c2 <- rnorm(20, .09, .02) d3.c1 <- rnorm(20, .11, .02) d3.c2 <- rnorm(20, .11, .02) group1 <- cbind(1, d1.c1, d2.c1, d3.c1) group2 <- cbind(2, d1.c2, d2.c2, d3.c2) colnames(group1) <- colnames(group2) <- c("group", "dim1", "dim2", "dim3") combined <- rbind(group1, group2) combined[,2:4] <- combined[,2:4] > .1 ctables <- xtabs(~., data = combined) loglm(~group+dim1+dim2+dim3, data=ctables) Call: loglm(formula = ~group + dim1 + dim2 + dim3, data = ctables) Statistics: X^2...

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]) env_var[tmp.keep=="TRUE"] } where env_var = a variable to be identified (e.g. plot IDs as in > row.names(dataframe)) ord = ordination points or scores created...

foo <- rnorm(30*34*12) dim(foo) <- c(30, 34, 12) I want to make a data.frame out of this three-dimensional array. Each dimension will be a variabel (column) in the data.frame. I know how this can be done in a very slow way using for loops, like this: x <- rep(seq(from = 1, to = 30), 34) y <- as.vector(sapply(1:34, function(x) {rep(x, 30)})) month <- as.vector(sapply(1:12,

...'m new with R and I can't find answer in packages doc. best regards, Claire Pujoll Paris, France library(marray) library(limma) ....... Rawdata <- read.GenePix(targets=Macro_Mono_targets,skip=107) design<- cbind(individual=c(0,0,1,1,2,2,3,3,4,4,5,5), dim1=c(1,0,1,0,1,0,1,0,1,0,1,0),dim2=c(0,1,0,1,0,1,0,1,0,1,0,1)) fit <- lmFit(normdata@maM, design) contrast.matrix<-makeContrasts(dim1vsdim2=dim2-dim1, levels=design) fit2 <- contrasts.fit(fit,contrast.matrix) fiteb <- eBayes(fit2) Toptable <- topTable(fiteb,number = 10600,genelist=maGeneTable(normdata), sort.by=&quo...

...0) >Predictors<-as.data.frame(read.csv("Predictors.csv",header=TRUE, sep = ",")) >Fish.fit <- envfit(Fish.mds$points, Predictors, k=3, 1000, na.rm = TRUE) >Fish.fit The output of Fish.fit was as follows (table truncated): Dim1 Dim2 r2 Pr(>r) DrainArea -0.5923233 -0.8057004 0.7674 0.000999 *** Flow -0.5283236 -0.8490431 0.7847 0.000999 *** StrmWidth -0.6993457 -0.7147836 0.6759 0.000999 *** Gradient 0.4541225 0.8909392 0.2085 0.01098...

Hi suppose I have two arrays x1,x2 of dimensions a1,b1,c1 and a2,b2,c2 respectively. I want x = x1 "+" x2 with dimensions c(max(a1,a2), max(b1,b2),max (c1,c2)) with x[a,b,c] = x1[a1,b1,c1] + x2[a2,b2,c2] if a <=min(a1,a2) , b<=min (b1,b2), c<=min(c1,c2) and the other bits either x1 or x2 or zero according to whether the coordinates are "in range" for

I want to make such plot using the following data set plot Mean with Sd(+/-) by Dim group by Lac here is data Does anyone know how to plot using xyploy Thanks, Aimin Mean Sd Var Min Max Dim Lac 704 44.00000 NA NA 44.0 44.0 -30 3 703 45.92000 9.5484030 91.1720000 60.0 34.4 -30 4 702 57.40000 NA NA 57.4 57.4 -30

...57782553 16 -0.003048803 0.0128157261 17 -0.051281437 0.0278941743 18 -0.051819085 0.0004327598 19 -0.072814626 0.0195622280 20 -0.072814626 0.0195622280 And in SAS's corresp output: Row Coordinates Dim1 Dim2 1 1.0607 -0.8155 2 0.7706 0.6346 3 1.0703 -1.3067 4 1.0703 -1.3067 5 0.2308 0.9000...

Buenos días -- Francisco Maturana Miranda Dr. Planificación territorial, urbanismo y dinámicas del espacio Profesor Asociado, Departamento de Geografía Universidad Alberto Hurtado www.fmaturana.cl [[alternative HTML version deleted]]

...385 771 1089.243 771 1156 20019 1000 a > dim_illegal(x) 0 1 161.480 1 386 2311 1000 a > sum(x) 10395 15784 16459.454 15785 16169 114333 1000 c > > So, my best shot on the original problem would now be to either use: > > dim2 <- function(x) dim(x) > foo <- function(x, dim=dim2(x)) { dim } > > or simply avoid the name clash via: > > foo <- function(x, dimx=dim(x)) { dimx } I think you'll find that baseenv()$dim(x) and .BaseNamespaceEnv$dim(x) are about 25 times faster than base::dim(x). T...

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]]

...file for, which is much easier to handle than 52 tables. I tried the following for the first dataset (i.e first week): W01<-read.table("RN_weekly/KW01_RN.dat") long<-W01$V1 lat<-W01$V2 RN01<-W01$V3 dim1 <- dim.def.ncdf( "EW","degrees", as.double(long)) dim2 <- dim.def.ncdf( "SN","degrees", as.double(lat)) varz <- var.def.ncdf("Radon","Bq/m2/h1", list(dim1,dim2), -1, longname="Radon flux rate") nc.rn <- create.ncdf("rn_weekly.nc",varz) put.var.ncdf(nc.rn,varz,RN01) close....

...the rows where [,162,] != NA....this will create a ragged array where the number of counts per sitesurvey varies outdata (dim1 varies from 1,22...ragged, 162,56). Step 2) from the extracted list, I would like to randomly select n rows (say for example, 3) outdata (dim1=2 or 3 counts(samples), dim2=162, dim3=56) Step 3) I need to sum the values from the columns of dimension 1 from step 2 s outdata (dim1=1 (column sums), dim2=162, dim3=56) Not sure how clear I've explained this, but any suggestions would be really helpful. Most appreciatively: Brian Campbell -- View...

Hello there I wish to get the "coordinates" of the minimum element of an array. For example, if the array were > H = array(c(8:5,1:4),dim=c(2,2,2)) > H , , 1 [,1] [,2] [1,] 8 6 [2,] 7 5 , , 2 [,1] [,2] [1,] 1 3 [2,] 2 4 then > min(H) [1] 1 and > max(H) [1] 8 Say "idx" were the function I'm looking for. Then, what