search for: y13

...ta looks like this: X1 (group index), Y11 (measurement), error of Y11 (error in measurement) X2, Y21, error of Y21 ... Xn, Yn1, error of Yn1 // End of the first set of measurements X1, Y12, error of Y12, X2, Y22, error of Y22, ... Xn, Yn2, error of Yn2 // End of the second set of measurements X1, Y13, error of Y13, X2, Y23, error of Y23, ... Xn, Yn3, error of Yn3 // end of the third set of measurements I need to put one errbar plot that include all three cases with different symbols for each data set. How can I do this? Thanks in advance. Youngjin [[alternative HTML version deleted]]

...1 2 X115 X116 X21 X22 X23 X24 X25 X26 X27 X28 X29 X210 X211 X212 1 2 0 1 0 1 1 1 0 1 0 1 0 1 X213 X214 X215 X216 Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Y9 Y10 1 1 0 1 1 2 3 4 5 6 7 8 1 2 Y11 Y12 Y13 Y14 Y15 Y16 3 4 5 6 7 8 So, e.g. for a 3 column matrix: > matrix(do.call(c,imp), ncol=3) [,1] [,2] [,3] [1,] 1 0 1 [2,] 2 1 2 [3,] 1 0 3 [4,] 2 1 4 [5,] 1 1 5 [6,] 2 1 6 [7,] 1 0 7 [8,] 2 1...

Hello everyone, I want to transform a data.frame into an array (lets call it mydata), where: mydata[[1]] is the first imputed dataset...and for each mydata[[d]], the first p columns are covariates X, and the last one is the outcome Y. Lets assume a simple data.frame: Imputed = data.frame( X1 = c(1,2,1,2,1,2,1,2, 1,2,1,2,1,2,1,2), X2 =

...1 2 X115 X116 X21 X22 X23 X24 X25 X26 X27 X28 X29 X210 X211 X212 1 2 0 1 0 1 1 1 0 1 0 1 0 1 X213 X214 X215 X216 Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Y9 Y10 1 1 0 1 1 2 3 4 5 6 7 8 1 2 Y11 Y12 Y13 Y14 Y15 Y16 3 4 5 6 7 8 So, e.g. for a 3 column matrix: > matrix(do.call(c,imp), ncol=3) [,1] [,2] [,3] [1,] 1 0 1 [2,] 2 1 2 [3,] 1 0 3 [4,] 2 1 4 [5,] 1 1 5 [6,] 2 1 6 [7,] 1 0 7 [8,] 2 1...

...gene expression divergence and 14 matrices which stands for gene sequence divergence. I have tried joining them by using the concatanation function giving SequenceDivergence <- c(X1,X2,X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13,X14) ExpressionDivergence <- c(Y1,Y2,Y3,Y4,Y5,Y6,Y7,Y8,Y9,Y10,Y11,Y12,Y13,Y14) where X1,X2..X14 are the expression matrices containing r-values and Y1,Y2..Y14 are the ones with patristic distances Now, I want to plot SequenceDivergence vs. Expression Divergence Tried doing that using plot (Sequence Divergence vs. Expression Divergence) But then getting the error...

...gene expression divergence and 14 matrices which stands for gene sequence divergence. I have tried joining them by using the concatanation function giving SequenceDivergence <- c(X1,X2,X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13,X14) ExpressionDivergence <- c(Y1,Y2,Y3,Y4,Y5,Y6,Y7,Y8,Y9,Y10,Y11,Y12,Y13,Y14) where X1,X2..X14 are the expression matrices containing r-values and Y1,Y2..Y14 are the ones with patristic distances Now, I want to plot SequenceDivergence vs. Expression Divergence Tried doing that using plot (Sequence Divergence vs. Expression Divergence) But then getting the error...

After searching in R- Introduction, FAQ, help... I don't understand this: I write a function in a file (.R): tt <- function(mc) { date() mc<-read.csv2("machines.txt",na.strings="") date() } I source it in R and I type tt(). The answer is > tt() [1] "Mon Aug 14 11:18:25 2000" > The instructions following the first "date()" are ignored. Why?

Hi All, I am making a serious effort to try to learn R, but one hurdle I am facing is that I need to "see" the data as I walk through the examples in the packages. For instance, many examples on the web start by a command like data("wines"). How can I actually view what the dataset looks like prior to transformations and analysis? I have tried to use edit() , print, and