similar to: Odd subsetting behaviour

Consider the following code: test <- function(n) { for(x in 1:n) { for(y in 1:n) { for(r in max(x-1,1):min(x+1,n)) { for(s in max(y-1,1):min(y+1,n)) { vec <- c(x-r,y-s) print(c("vec = ", vec)) print(identical(vec,c(0,0))) } } } } } If you run test(2) you'll see a printout of the values

Hi, suppose I have a matrix (or dataframe) as a result from subsetting. mat <- matrix(1:20,ncol=2) mat[c(3,6,9),] <- NA cc <- complete.cases(mat) sub <- mat[cc,,drop=FALSE] sub <- sub * 2 #some caluculations with sub. now I would like to expand sub somehow so row 3,6, and 9 would be filled with NAs but the rest should be in place again. Is there a simple function for this?

Hello! All, I am working on 10000x1000 matrix say 'mat' and i want to subset this matrix in a fashion that in new matrix i get columns 2,3,9,10,16,17,23,24.......so on. That is pair of columns after every interval of 7. I tried following but i got an error which is obvious. >dim(mat) [1] 10000 10 >a=mat[,c(seq(c(2,3),ncol(mat),7))] Warning messages: 1: In if (n < 0L)

Hello, I have a question about list indexing. Lets say we have a list of 3 lists, each containing 3 different type elements: > a=replicate(3, list(list(c(1,1,1), diag(3), c(2,2,2)))) > a [[1]] [[1]][[1]] [1] 1 1 1 [[1]][[2]] [,1] [,2] [,3] [1,] 1 0 0 [2,] 0 1 0 [3,] 0 0 1 [[1]][[3]] [1] 2 2 2 [[2]] [[2]][[1]] [1] 1 1 1 [[2]][[2]] [,1] [,2] [,3]

Hi This is a difference between the way matrices and data frames work I guess. I want to replace the NA values in a data frame by 0, and the code works as long as the data frame in question actually includes an NA value. If it doesn't, there is an error: df <- data.frame(c1=c(1,1,1),c2=c(2,2,NA)) df[is.na(df)] <- 0 df df <- data.frame(c1=c(1,1,1),c2=c(2,2,2)) df[is.na(df)] <-

Dear sirs, 1...........Kindly tell me is it possible to form a matrix which contains a no of matrices.. for eg.. if a,b,c,d are matrices.... and e is a matrix which contains a,b,c,d as rows and columns.. 2..........Is it possible to form array of array of arrays for eg.. "A" contains two set of arrays (1,2)...and each A[1] and A[2] individually contains two set of arrays I tried like

Dear R-community, my data set looks like 'mat' below. Plant<-c(NA,1,1,1,NA,NA,NA,NA,NA,1); Value1<-rnorm(1:10); Value2<-rnorm(1:10); mat<-cbind(Plant,Value1,Value2); I receive data from two different sites. One site is identified by an interger number, the other site has no data in column Plant=NA. My pb: I'm trying to assign labels "A" or "B" to

Dear R experts, I have two matrix (seq & mat) & I want to retrieve in a new matrix all the numbers from mat that =1 (corresponding to the same row/ column position) in seq, or all the numbers in mat that =-1 in seq. - Replace all the numbers with NA if it's not 1/-1 in seq. There are some "NA"s in seq. seq=matrix(c(1,-1,0,1,1,-1,0,0,-1,1,1,NA),3,4)

Hi, Rui and Michael, thank you both for replying. Yeah, I'm not supposed to know about Chi-squared yet. So far, all of our work with hypothesis tests has involved creating the sample data, then resampling it to create a null distribution, and finally computing p-values. The prop.test() would work. obviously. I'll look into that. I didn't know about it. I'm really struck by the

Hello everyone, Considering the following code sample : ---- indexes <- function(vec) { vec <- which(vec==TRUE) return(vec) } mat <- matrix(FALSE, nrow=10, ncol=10) mat[1,3] <- mat[3,1] <- TRUE ---- Issuing apply(mat, 1, indexes) returns a 10-cell list, as expected. Now if I do: ---- mat[1,3] <- mat[3,1] <- FALSE apply(mat, 1, indexes) ---- I would expect a

Can anyone explain this? I have a matrix with double components. It's taking up a lot of memory, so I want to multiply then turn it to integers. I'm pretty certain that there are only 2 decimal places, but I wanted to check by using modulo. E.g. mat = matrix(11:50/100, ncol=4,nrow=10) #Matrix with values out to the hundredths any((mat * 100)%%1!=0) But oddly enough it doesn't work.

I have a matrix of p-values for for each explanatory variable. Each row is an area of the response variable and each column is an explanatory variable. e.g. PSA pval_DOY pval_PDSIconcurrent pval_PDSIantecedent_annual_average pval_TMAXanomaly pval_FM100anomaly 1 NC06 0.96747495 0.6092668 0.53353019 0.9301115 0.99801334 2 NC04 0.04699659

Hi list, I want to find the total maximum resources I can spend given a set allocation proportion and some simple budget constraints. However, I get suboptimal results via lp and friends (i.e. lpSolve and simplex in the linprog and boot) . For example: library(lpSolve) proportions = c( 0.46, 0.28, 0.26) constraints = c( 352, 75, 171) lp(objective.in = proportions, const.mat =

I ran into a problem with "subset" while working at home that I am not sure is a bug or not. I defined a custom function to take a data frame of tree positions, sizes, and types (containing the columns TRT, COMP, PLOT, X, Y, DBH and CON) and wanted to make a stem map of the plot using different symbols and colors to represent the different types of tree stems. I copied a bit of the

Dear R users, I have a response variable in a csv file called "y" and a matrix of predictor variables in a csv file called "mat". I have used the function "nls" I have specified the nonlinear relation between these variable.The code I have witten is called Rprog which begins with the phrase: L.minor.m1<-nls(Y~a ....etc.. The program when I execute the program, I

Dear R-Helpers, I am working on a dataset containing ca. 500 specimens of 17 different species. The data is three text columns, followed by ca 70 columns of binary data. I'm trying to write a function that will allow me to interactively exclude species using the inofrmation in the third text column. My function, matrix.slicer, appears to work as I intend. However, when I pass the

Hi everyone, I've got the following problem: I've got a matrix [1000,2] and two vectors. In very matrix row there is two coefficients b0 and b1. The vectors are two variables x and y. I want to do a loop to take b0 and b1 and with x and y calculate the residual of a linear model and calculate the second order coefficient of autocorrelation. What I did is : rho<-function(mat, x,y){

Hi Michael and Abby, So one thing that could happen that would be backwards compatible (with the exception of something that was an error no longer being an error) is head and tail could take vectors of length (dim(x)) rather than integers of length for n, with the default being n=6 being equivalent to n = c(6, dim(x)[2], <...>, dim(x)[k]), at least for the deprecation cycle, if not

During some experimentation in preparing R lessons I encountered this behaviour which I can not explain fully mat <- matrix(1:16, 4,4) df1 <- data.frame(mat) > mean(df1) X1 X2 X3 X4 2.5 6.5 10.5 14.5 Expected, documented > median(df1) [1] 6.5 10.5 Rather weird, AFAIK there shall not be an issue with data frame at least I did not find any in help page. I tracked it

Dear all, I have a problem with the "subset()" function. I spent all day yesterday with a collegue to solve it and we did not find a satisfying solution (even in the archived mails), so I ask for your help. Let's say (for a simple example) a matrix mat: R> mat cola colb colc [1,] 1 4 7 [2,] 2 5 8 [3,] 3 6 9 My goal is to select the lines of the matrix on the basis of the