search for: dim1

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 shoul...

...-lm */ #include <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 (si...

...18580836 0.3218897 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 0.2463...

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 matrix...

....10, .02) d2.c1 <- 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:...

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 cre...

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,

Hi all, I'm trying to do model reduction for logistic regression. I have 13 predictor (4 continuous variables and 9 binary variables). Using subject matter knowledge, I selected 4 important variables. Regarding the rest 9 variables, I tried to perform data reduction by principal component analysis (PCA). However, 8 of 9 variables were binary and only one continuous. I transformed the data by

...aracter(lapply(gens, function(g) g[[2]])) seqs <- lapply(gens, function(g) g[[3]]) .LC <- comprehend(expr, vars, seqs) ## Provided the result is rectangular, convert it to a vector or array ## TODO: Extend to handle .LC structures more than 2-deep. if(!length(.LC)) return(.LC) dim1 <- dim(.LC[[1]]) if(is.null(dim1)){ lengths <- sapply(.LC, length) if(all(lengths == lengths[1])){ # rectangular .LC <- unlist(.LC) if(lengths[1] > 1) # matrix dim(.LC) <- c(lengths[1], length(lengths)) } else { # ragged # leave .LC as a list...

...from my data ? I'm sorry, i'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=maG...

...ot;,k=3,trymax=20) >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...

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

...,162,] is the index that represents whether a survey had been conducted or not...sitesurvey total OK, here is where I need help; Step 1) I need to extract from new.mydata1 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),...

...68229 0.0357782553 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]]

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]]

...coordinates but other values, i.e. time series. Now I want to create a NetCDF 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 <- c...

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

...850 0.7172834 h3 0.8941212 0.7257939 0.5631331 0.5815922 h4 0.8487089 0.6284291 0.4226977 0.4107244 , , a1, w2................................ I thought it would be something along the lines of apply(4Darray, c(1,2,3), function(x) x*3Darray). But this returns the results in the form of 64rows by dim1 by dim2 by dim3. , , i4, a4 h1 h2 h3 h4 [1,] 8.05058486 6.881337e+00 5.579569e+00 3.940329195 [2,] 0.19306289 2.185652e-01 2.347175e-01 0.219540239 . . . [63,] 0.00000000 1.300468e-01 2.430320e-01 0.395577205 [64,] 0.00000000 0.000000e+...