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...ng). I have been wanting to drop all the rows if there values are `NA' or have specific values like 1 or 2 or 3. mdat <- matrix(1:21, nrow = 7, ncol=3, byrow=TRUE, dimnames = list(c("row1", "row2","row3","row4","row5","row6","row7"), c("C.1", "C.2", "C.3"))) mdat<-data.frame(mdat) mdat C.1 C.2 C.3 row1 1 2 3 row2 4 5 6 row3 7 8 9 row4 10 11 12 row5 13 14 15 row6 16 17 18 row7 19 20 21 I want to say drop...

...gave up: I have a 2-dimensional array, and I know how to split it into its rows and how to get the mean for every row using 'sapply'. But what I want is to calculate the mean over the first n rows, and then the second n rows, etc., so that I get a vector like: v == mean1(row 1:5), mean2(row6:10),... (trivial, you might say. I find it rather mind-boggling, though: I tried to get the mean from the array before splitting it, after splitting it, looping through it with for-loops...I feel like an idiot by now; looks like I missed a crucial point of how 'R' works.) Thanks a lot...

...t: Estimate Std. Error t value Pr(>|t|) (Intercept) 7.64459 NA NA NA Row2 -0.05467 NA NA NA Row3 0.24541 NA NA NA Row4 0.42035 NA NA NA Row5 0.43961 NA NA NA Row6 0.04532 NA NA NA Row7 -0.04881 NA NA NA Row8 0.25370 NA NA NA Row9 -0.14976 NA NA NA Row10 -0.01267 NA NA NA Col2 0.69283 NA NA NA Col3...

I guess this has a simple solution: I have matrix 'mat1' which has row and column names, e.g.: A B C row1 0 0 0 row2 0 0 0 .... rown 0 0 0 I have a another matrix 'mat2', essentially a subset of 'mat1' where the rownames are all in 'mat1' e.g.: B row3 5 row8 6 row54 7 I want to insert the values of matrix mat2 for column B (in reality it could be some or

Hi, Given a positive integer N, and a real number \lambda such that 0 < \lambda < 1, I would like to generate an N by N stochastic matrix (a matrix with all the rows summing to 1), such that it has the second largest eigenvalue equal to \lambda (Note: the dominant eigenvalue of a stochastic matrix is 1). I don't care what the other eigenvalues are. The second eigenvalue is

...row = 10, ncol = 3); edit(mat, edit.row.names = TRUE) col1 col2 col3 row1 0.6185206 0.32911907 -0.12263839 row2 0.4553981 -1.77532265 2.06745757 row3 0.4676557 0.58817426 -0.30507048 row4 1.1898153 -1.24888167 1.02240513 row5 -1.4809138 0.05212133 0.25272844 row6 1.5709981 -1.87496256 -0.05699266 row7 0.3770318 -0.43538598 -1.28299648 row8 1.3900096 0.15139637 -1.01168270 row9 -0.3973376 0.05933193 0.34420058 row10 -1.4248380 0.86637712 -1.25193470 > q() when the matrix is simply saved from the editor -- ie no segfault. Hope this helps, and...

...t.row.names = TRUE) > col1 col2 col3 > row1 0.6185206 0.32911907 -0.12263839 > row2 0.4553981 -1.77532265 2.06745757 > row3 0.4676557 0.58817426 -0.30507048 > row4 1.1898153 -1.24888167 1.02240513 > row5 -1.4809138 0.05212133 0.25272844 > row6 1.5709981 -1.87496256 -0.05699266 > row7 0.3770318 -0.43538598 -1.28299648 > row8 1.3900096 0.15139637 -1.01168270 > row9 -0.3973376 0.05933193 0.34420058 > row10 -1.4248380 0.86637712 -1.25193470 >> q() > > when the matrix is simply saved from the editor -- ie no...