similar to: How to get rid of loop?

Hi all, I've got a matrix of fractional data that is all positive and greater than zero that I would like to "loosely" classify, for lack of a better word. It looks something like this : 1.07 1.11 1.27 1.59 0.97 0.76 2.23 0.98 0.71 0.88 1.19 1.02 What I'm looking for is a way to round these numbers to the nearest 0.25, i.e. the above matrix would be

> as.character(seq(-.25,.95,.1)) [1] "-0.25" "-0.15" "-0.05" "0.05" "0.15" "0.25" "0.35" "0.45" "0.55" "0.65" "0.75" "0.85" "0.95" > as.character(seq(-.35,.95,.1)) [1] "-0.35" "-0.25"

Hi all, I have a matrix of 474 rows (samples) with 565 columns (variables). each of the 474 samples belong to one of 120 groups, with the groupings as a column in the above matrix. For example, the group column would be: 1 1 1 2 2 2 . . . 120 120 I want to randomly select one from each group. Not all the groups have the same number of samples, some have 4, some 3 etc. Is there a function to

Hi, I'm trying to create a distance matrix. And it works out somewhat ok. However, I suspect that there are some efficiency issues with my efforts. Plz have a look at this: donor <- matrix(c(3,1,2,3,3,1,4,3,5,1,3,2), ncol=4) receiver <- matrix(c(1,4,3,2,4,3,1,5,1,3,2,1,4,5,3,5,1,3,2,4,5,1,2,3,1,4,5,5,1,2,1,3,4,3,2,5,5,1,4,2,5,4,3,2), ncol=4) The above creates my two matrices. I have

Hi, I am trying to use (i) as an index but R considers it as a function and not as text. To be more specific I would like for example to estimate some regressions named qrnox1, qrnox2, qrnox3,..... and so on. But when I am using qrnox(i) ot qrnox[i] it tries to find the ith element of vector qrnox. The thing is that I want to estimate the qrnoxi regression and not the qrnox(i) function or

Hi R-helpers, I would like to subset my dataframe, keeping only those rows which satisfy the following conditions: 1) the string "dnv" is found in at least one column; 2) the value in the column previous to the one "dnv" is found in is not "0" Here's what my data look like: ??? POND_ID 2009-05-07 2009-05-15 2009-05-21 2009-05-28 2009-06-04 4 ? ? ? 101 ? ? ?

Hey all, The code below creates a partial dependence plot for the variable x1 in the linear model y ~ x1 + x1^2 + x2. I have noticed that the for loop in the code takes a long time to run if the size of the data is increased. Is there a way to change the for loop into an apply statement? The tricky part is that I need to change the values of x1 in each step of the loop to give me the

I try to utilize some operations on rows in a matrix using command 'apply' but find a problem. First I write a simple function to normalize a vector (ignore error handling) as follows: normalize = function( v ) { return( ( v-min(v) ) / ( max(v) - min(v) ) ) } The function works fine for a vector: > normalize( 1:5 ) [1] 0.00 0.25 0.50 0.75 1.00 Then I generate a matrix: > a =

Dear all, I would like to ask one question related to statistics, for specifically on defining dummy variables. As of now, I have come across 3 different kind of dummy variables (assuming I am working with Seasonal dummy, and number of season is 4): > dummy1 <- diag(4) > for(i in 1:3) dummy1 <- rbind(dummy1, diag(4)) > dummy1 <- dummy1[,-4] > > dummy2 <- dummy1 >

Hi, I'm stuck on creating a plot with x tick labels for every Nth tick mark - how is that done? I don't see a simple solution to this in help(plot) or help(par) and what I've tried is not working, eg, the following does not work, although it seems intuitive to me that it should work: x <- seq(-100,1000,25) y <- x * x % find all the x values that are multiples of 100 tmp <-

Folks, The contour() function wants x and y to be in increasing order. I have a situation where I have a grid in x and y, and associated z values, which looks like this: x y z [1,] 0.00 20 1.000 [2,] 0.00 30 1.000 [3,] 0.00 40 1.000 [4,] 0.00 50 1.000 [5,] 0.00 60 1.000 [6,] 0.00 70 1.000 [7,] 0.00 80 0.000 [8,] 0.00 90

I have panel data in the following form: TIME X1 S1 1 1 0.99 1 2 0.50 1 3 0.01 2 3 0.99 2 1 0.99 2 2 0.25 3 3 0.75 3 2 0.50 3 1 0.25 ... ... ...... And desire a new vector of observations in which one column (S1 above) is sorted for each second from least to largest. That

useR's, This is a follow up question to one I previously asked. Consider the 3-element list below > res [[1]] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [1,] NA NA NA 1.25 0.25 0.75 NA NA NA NA NA NA 1.25 0.25 [2,] 1.25 0.25 0.75 NA NA NA NA NA NA 1.25 0.25 0.75 NA NA [3,] NA NA NA NA NA

useR's, I am trying to find a quick way to change some values in a list that are subject to a condition to be NA. Consider the 3x1 matrix: delta <- matrix(c(2.5,2.5,1), nrow = 1) And consider the list named v that has 3 elements > v v[[1]] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [1,] 4.25 3.25 2.25 1.25 0.25 0.75 1.75 2.75 3.75 4.25

useR's, Does anyone know of an efficient way to change the values in a list to different numbers stored in an object? For example, consider the following: y <- matrix(c(20, 13, 25, 10, 17), ncol = 1) > res [[1]] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [1,] NA NA NA 1.25 0.25 0.75 NA NA NA NA NA NA 1.25 0.25 [2,]

I start a clean session of R 1.9.1 on Windows and I run the following code: > library(MASS) > data(painters) > pca.painters <- princomp(painters[ ,1:4]) > loadings(pca.painters) Loadings: Comp.1 Comp.2 Comp.3 Comp.4 Composition 0.484 -0.376 0.784 -0.101 Drawing 0.424 0.187 -0.280 -0.841 Colour -0.381 -0.845 -0.211 -0.310 Expression 0.664 -0.330 -0.513

Estimado Mauricio Monsalvo Le paso una idea, no es un código muy lindo que digamos, pero al correrlo seguramente se dará cuenta de mi sugerencia. datos<-c(2,3,4,5,6,7,8) quantile(datos) quantile(datos,probs = c(0.25, 0.75, 0.85, 0.90, 0.95)) as.matrix(quantile(datos,probs = c(0.25, 0.75, 0.85, 0.90, 0.95))) as.data.frame(quantile(datos,probs = c(0.25, 0.75, 0.85, 0.90, 0.95))) # ¿ y si solo

Dear list I'm testing a predictor and I produced nice performance plots with ROCR package utilizing the 3 standard command pred <- prediction(predictions, labels) perf <- performance(pred, measure = "tpr", x.measure = "fpr") plot(perf, col=rainbow(10)) The pred object and the perfo object are S4 with the following slots An object of class "performance"

Habría que buscar la vuelta, yo no lo se, pero posiblemente lo siguiente da una pista. Nota: al mismo código le sume una línea al final datos<-c(2,3,4,5,6,7,8) quantile(datos) quantile(datos,probs = c(0.25, 0.75, 0.85, 0.90, 0.95)) as.matrix(quantile(datos,probs = c(0.25, 0.75, 0.85, 0.90, 0.95))) as.data.frame(quantile(datos,probs = c(0.25, 0.75, 0.85, 0.90, 0.95))) # ¿ y si solo solicita

Hi All, I want to create a categorical variable, cat.pfoa, in the file of pfas.pheno (a data frame) based on log2pfoa values. I can do it using the following code. pfas.pheno <-within(pfas.pheno, {cat.pfoa<-NA cat.pfoa[pfas.pheno$log2pfoa <=quantile(pfas.pheno$log2pfoa,0.25, na.rm =T)]<-0 cat.pfoa[pfas.pheno$log2pfoa >=quantile(pfas.pheno$log2pfoa,0.75, na.rm =T)]<-2