similar to: how to rename rows/columns of a matrix?

Displaying 20 results from an estimated 6000 matches similar to: "how to rename rows/columns of a matrix?"

2007 Mar 10
3
long character string problem
Hi All I am having 2 very long character strings (550chars) and I want to put them as expressions together with c(). The problem is that I also get these double-quotes, as seen below in 'fct'. How can I remove these double-quotes? I tried as.name() but it did not work (because of size?). These are creating trouble with subsequent programs, which I tested with strings that for some
2003 Jul 15
2
matrix manipulations
Hi cor(x,apply(x,1,sum)) gives me the correlations of each column with the sums of each row (correct me if I'm wrong, please). What I need are the correlations of each column with the sums of each row except the entry in the given column. It seems that for any one column i I get it by doing: cor(x[,i],apply(x[,-i],1,sum)) But I struggle to get it for all the columns. I was trying things
2018 Feb 20
5
Take the maximum of every 12 columns
Dear all, I have monthly data in wide format, I am only providing data (at the bottom of the email) for the first 24 columns but I have 2880 columns in total. I would like to take max of every 12 columns. I have taken the mean of every 12 columns with the following code: byapply <- function(x, by, fun, ...) { # Create index list if (length(by) == 1) { nc <- ncol(x)
2003 Jul 08
7
rbind question
Hi I am trying to replicate a vector in n rows for comparison purposes with another matrix. foo <- c(1,2,3) bar <- rbind(foo,foo) # does the trick for 2 rows bar <- rbind(rep(foo,2)) # does something else How do I generate a matrix with all rows=foo without writing 'foo' n times as arg? Thanks, David
2004 Mar 09
2
use of split lines in ess
Hi all I am very astonished that R generates a "syntax error" when I want to split up a line with a backslash, which usually works in any shell script. R itself generates the "+" symbols at the beginning of following lines in a splitted line so I've tried with them as well, but also without success. Searching in the h-help archive did not reveal any answer either.
2018 Feb 20
3
Take the maximum of every 12 columns
This is what I was looking for. Thank you everyone! Sincerely, Milu <https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail> Mail priva di virus. www.avast.com <https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail>
2004 Sep 21
3
how to take this experiment with R?
How about: x <- data.frame(matrix(rnorm(1550),c(50,31))) model <- step(lm(x[,1] ~ as.matrix(x[,2:31]))) --Matt -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch]On Behalf Of rongguiwong Sent: Monday, September 20, 2004 20:52 PM To: r-help at stat.math.ethz.ch Subject: [R] how to take this experiment with R? This message uses
2005 Aug 15
2
queer data set
I have a dataset that is basically structureless. Its dimension varies from row to row and sep(s) are a mixture of tab and semi colon (;) and example is HEADER1 HEADER2 HEADER3 HEADER3 A1 B1 C1 X11;X12;X13 A2 B2 C2 X21;X22;X23;X24;X25 A3 B3 C3 A4 B4 C4 X41;X42;X43 A5 B5 C5 X51 etc., say. Note that a blank
2018 Feb 20
0
Take the maximum of every 12 columns
Ista, et. al: efficiency? (Note: I needed to correct my previous post: do.call() is required for pmax() over the data frame) > x <- data.frame(matrix(runif(12e6), ncol=12)) > system.time(r1 <- do.call(pmax,x)) user system elapsed 0.049 0.000 0.049 > identical(r1,r2) [1] FALSE > system.time(r2 <- apply(x,1,max)) user system elapsed 2.162 0.045 2.207 ##
2018 Feb 20
0
Take the maximum of every 12 columns
Hi Milu, byapply(df, 12, function(x) apply(x, 1, max)) You might also be interested in the matrixStats package. Best, Ista On Tue, Feb 20, 2018 at 9:55 AM, Miluji Sb <milujisb at gmail.com> wrote: > Dear all, > > I have monthly data in wide format, I am only providing data (at the bottom > of the email) for the first 24 columns but I have 2880 columns in total. > > I
2006 Mar 11
1
Non-linear Regression : Error in eval(expr, envir, enclos)
Hi.. i have an expression of the form: model1<-nls(y~beta1*(x1+(k1*x2)+(k1*k1*x3)+(k2*x4)+(k2*k1*x5)+(k2*k2*x6)+(k3*x7)+(k3*k4*x8)+(k3*k2*x9)+(k3*k3*x10)+ (k4*x11)+(k4*k1*x12)+(k4*k2*x13)+(k4*k3*x14)+(k4*k4*x15)+(k5*x16)+(k5*k1*x17)+(k5*k2*x18)+(k5*k3*x19)+
2006 Nov 06
5
memory issues with new release (PR#9344)
Full_Name: Derek Elmerick Version: 2.4.0 OS: Windows XP Submission from: (NULL) (38.117.162.243) hello - i have some code that i run regularly using R version 2.3.x . the final step of the code is to build a multinomial logit model. the dataset is large; however, i have not had issues in the past. i just installed the 2.4.0 version of R and now have memory allocation issues. to verify, i ran
2018 Feb 20
2
Take the maximum of every 12 columns
Don't do this (sorry Thierry)! max() already does this -- see ?max > x <- data.frame(a =rnorm(10), b = rnorm(10)) > max(x) [1] 1.799644 > max(sapply(x,max)) [1] 1.799644 Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic
2018 Feb 20
2
Take the maximum of every 12 columns
On Tue, Feb 20, 2018 at 11:58 AM, Bert Gunter <bgunter.4567 at gmail.com> wrote: > Ista, et. al: efficiency? > (Note: I needed to correct my previous post: do.call() is required for > pmax() over the data frame) > > > x <- data.frame(matrix(runif(12e6), ncol=12)) > > > system.time(r1 <- do.call(pmax,x)) > user system elapsed > 0.049 0.000
2018 Feb 20
0
Take the maximum of every 12 columns
The maximum over twelve columns is the maximum of the twelve maxima of each of the columns. single_col_max <- apply(x, 2, max) twelve_col_max <- apply( matrix(single_col_max, nrow = 12), 2, max ) ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team Biometrie
2011 Aug 20
2
a Question regarding glm for linear regression
Hello All, I have a question about glm in R. I would like to fit a model with glm function, I have a vector y (size n) which is my response variable and I have matrix X which is by size (n*f) where f is the number of features or columns. I have about 80 features, and when I fit a model using the following formula,? glmfit = glm(y ~ x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8 + x9 + x10 + x11 + x12 + x13
2017 Dec 21
2
[bug report] null ptr deref in nouveau_platform_probe (tegra186-p2771-0000)
Hi Thierry, Thanks for the patch. I applied on top of linux-next-2017-12-14. Different output this time. [ 11.862495] WARNING: CPU: 1 PID: 254 at drivers/gpu/drm/nouveau/nvkm/subdev/mmu/vmmgf100.c:391 gf100_vmm_new_+0x60/0x128 [nouveau] [ 11.863458] tegra-dpaux 155c0000.dpaux: 155c0000.dpaux supply vdd not found, using dummy regulator [ 11.866197] tegra-sor 15580000.sor: failed to probe
2003 Jun 17
1
How to generate a pairwise non-parametric comparison table?
Dear list I am comparing the results of several different experimental setups. With kruskal.test() I can test if there is any difference at all in any of them, if I understand it correctly. But now, when there is a difference, how do I generate a (half-) table of pairwise comparisons, using e.g. wilcox.test(), to find the ones where the difference actually occurs. I guess I don't have to
2018 Feb 20
0
Take the maximum of every 12 columns
Thank you for your kind replies. Maybe I was not clear with my question (I apologize) or I did not understand... I would like to take the max for X0...X11 and X12...X24 in my dataset. When I use pmax with the function byapply as in byapply(df, 12, pmax) I get back a list which I cannot convert to a dataframe. Am I missing something? Thanks again! Sincerely, Milu
2018 May 24
4
Manipulation of data.frame into an array
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 =