similar to: Multiple error bar plots

Hi all, I have a data.frame with the following colnames pattern: x1 y11 x2 y21 y22 y23 x3 y31 y32 ... I.e. I have an x followed by a few y's. What I would like to do is turn this wide format into a tall format with two columns: "x", "y". The structure is that xi needs to be associated with yij (e.g. x1 should next to y11 and y12, x2 should be next to y21, y22, and

II am translating some gauss code into R, and gauss has a matrix product function called the horizontal direct product (*~), which is some sort of variant on the Kronecker product. For example if x is 2x2 and y is 2x2 the horizontal direct product, z, of x and y is defined (in the Gauss manual) as: row 1 = x11*y11 x11*y12 x12*y11 x12*y12 row 2 = x21*y21 x21*y22 x22*y21 x22*y22 Or in R

Hi, We got a question about interpretating R-suqared. The actual outputs for a test dataset is X=(x1,x2, ..., xn). model 1 predicted the outputs as Y1=(y11,y12,..., y1n) model n predicted the outputs as Y2=(y21,y22,..., y2n) ... model m predicted the outputs as Ym=(ym1,ym2,..., ymn) Now we have two ways to calculate R squared to evaluate the average performance of committee model. (a)

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?

In the following code I have created the posterior density for a Bayesian survival model with four parameters. However, when I try to use the adapt function to perform integration in four dimensions (on my old version of R I get an error message saying that I have applied a non-function, although the function does work when I type kernel2(param0, theta0), or on the newer version of R the computer

This is one of those instances where a less superficial knowledge of R's technical details comes in really handy. What you need to do is convert the data frame to a single (numeric) vector for, e.g. a matrix() call. This can be easily done by noting that a data frame is also a list and using do.call(): ## imp is the data frame: do.call(c,imp) X11 X12 X13 X14 X15 X16 X17 X18 X19

Hello! let: test<-1:3 list(test) names(test)<-c("X11","X12","Y23") >test[["Y2"]] 3 I had assumed that the names in a list are like a keys in a hash. Therefore i thought that no value should be returned. The behavior of: >test["Y2"] <NA> NA is as i expected. Should it be as it is? How is the definition of [[]] and []?

Hello everyone, Thank you for this. Nonetheless it is not exactly want i need. I need mydata[[1]] to provide the values for all 3 variables (Y, X1 and X2) of the first imputation only. As it stands it returns the whole database. Any ideas? Best, ioanna ________________________________ From: Bert Gunter <bgunter.4567 at gmail.com> Sent: 24 May 2018 16:04 To: Ioanna Ioannou Cc:

Dear experts, I have in all 14 matrices which stands for 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

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 =

Dear experts, I have in all 14 matrices which stands for 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

--- "Paino, Christopher L YN1(AW) (CPF N0084)" <PainoCL@cpf.navy.mil> wrote: > If I am understanding FLAC correctly, the internal MD5 sum is (or can > be > )different than the fingerprint file sum. Yes. > The internal sum can be > different > depending on which compression settings are used, while the audio > remains > unchanged. It's the other way

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

Hi, Amazing work you folks have been doing! I don't know if this is the proper place to talk about this, but this looks like the best place to start! I've been messing with the latest version of FLAC and as an end-user I have this problem. The verification process currently does not use the fingerprint file during verification. So, only the integrity of the FLAC file is checked.

Dear all I am intrested in making iterative estimation (thro' loop statements) of, say, linear regression model. For this purpose, I have written the following programme and that I have made use of a sample data (viz., exp.txt): ? Programme: ? # Linear regression modelling with sample data (try5.txt) # Repeated estimation through loop statement

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-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hello, Here is my setup: dovecot - 2.2.11 pigeonhole - 0.4.2 qmail I was trying to create a vacation message, but after the sive script has been created and I was checking the logs I saw some strange errors: DOVECOT LOG Jun 18 16:52:24 lda(portase.florin at medianetork.ro): Error: lmtp client: connect(medianetork.ro, 25) failed: Connection

°_§É§¿§¿ ----- Original Message ----- From: <r-help-request at stat.math.ethz.ch> To: <r-help at stat.math.ethz.ch> Sent: Sunday, December 08, 2002 7:00 PM Subject: R-help digest, Vol 1 #10 - 6 msgs > Send R-help mailing list submissions to > r-help at stat.math.ethz.ch > > To subscribe or unsubscribe via the World Wide Web, visit >

Hi all, I have happened to work on MS .NET for sometime now, and I found that this language offers RNG what is called as Donald E. Knuth's subtractive random number generator algorithm (found here: http://msdn.microsoft.com/en-us/library/system.random.aspx#Y12). ? Here I was wondering whether R also have same RNG in it's inventory, so looked at ?set.seed. There I found 2 related RNGs

Hi all, I have a multiple-linear regression problem. There are 13 columns of data, the whole data matrix is: n x 13, where n is the number of samples. Now I want to regress EACH of the first 12 columns onto the 13th column, with 2-parameter linear model y_i = b0 + b1 * x_i, where i goes from 1 to n, and b0 is the intercept. How do I create a design matrix to do the 12-column regression