similar to: overlaying plots from a list of data frames

Hello, Suppose I have a matrix a where a= sp1 sp2 sp3 sp4 sp5 sp6 site1 1 0 1 1 0 1 site2 1 0 1 1 0 1 site3 1 1 1 1 1 1 site4 0 1 1 1 0 1 site5 0 0 1 0 0 1 site6 0 0 1 0 1 0 And I want to pack that matrix so that the upper left corner contains most of the ones and the bottom right corner contains most of the zeros so that matrix b is b= sp3 sp6 sp4 sp1 sp2 sp5 site1 1 1 1 1 0 0 site2

Dear all, I would like to multiply two matrixes with the different dimension column by column. Let make an example: If I have two matrixes "X" and "Y"as follow: X<- matrix(1:12, nrow=4, ncol=3, dimnames=list(c("A","B","C","D"), c("stage1","stage2","stage3"))) Y<- matrix(1:28, nrow=4, ncol=7,

I want to gain thousands of random sampling data by randomizing the presence-absence data. Meantime, one important limition is that the row and column sums must be fixed. For example, the data "tst" is following: site1 site2 site3 site4 site5 site6 site7 site8 1 0 0 0 1 1 0 0 0 1 1 1 0 1 0 1 1 0 0 0 1 0 1 0 0 0 0 1 0 1 0 1 1 0 1 0 0 0 0 0 0 1 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0

Dear r-users! I would like to cross two data frame which have the same row number but different in the number of column. Can anybody help me for this case ? Thanks a lot in advance -------------------------------------------------------------------------------- Majid Iravani PhD Student Swiss Federal Research Institute WSL Research Group of Vegetation Ecology Z?rcherstrasse 111

Thanks for everyone's input so far, it is greatly appreciated. But I've got one last task I could use some advice on Here are the first few lines of my data set: site,time_local,time_utc,reef_type_code,sensor_type,sensor_depth_m,temperature_c 06,2006-04-09 10:20:00,2006-04-09 20:20:00,BAK,sb39, 2, 29.63 06,2006-04-09 10:40:00,2006-04-09 20:40:00,BAK,sb39, 2, 29.56 06,2006-04-09

Dear list, I'm trying to mimic the analysis of Wedderburn (1974) as cited by McCullagh and Nelder (1989) on p.328-332. This is the leaf-blotch on barley example, and the data is available in the `faraway' package. Wedderburn suggested using the variance function mu^2(1-mu)^2. This variance function isn't readily available in R's `quasi' family object, but it seems to me

Dear List, I often have to merge two or more data frames containing unique row names but with some columns (names) common to the two data frames and some columns not common. This toy example will explain the kind of setup I am talking about: mat1 <- as.data.frame(matrix(rnorm(20), nrow = 5)) mat2 <- as.data.frame(matrix(rnorm(20), nrow = 4)) rownames(mat1) <- paste("site",