similar to: Inf and NA

Hi I am trying to create a loop which averages replicates in my data. The original data has many rows. and consists of 40 column zz[,2:41] plus row headings in zz[,1] I am trying to average each set of values (i.e. zz[1,2:3] averaged and placed in average_value[1,2] and so on. below is my script but it seems to be stuck in an endless loop Any suggestions?? for (i in 1:length(average_value[,1])) {

--- On Fri, 15/5/09, Amit Patel <amitrhelp at yahoo.co.uk> wrote: > From: Amit Patel <amitrhelp at yahoo.co.uk> > Subject: Help with loops > To: r-help at r-project.org > Date: Friday, 15 May, 2009, 12:17 PM > Hi > I am trying to create a loop which averages replicates in > my data. > The original data has many rows. and consists of 40 column > zz[,2:41]

Hi, May be this helps: ?set.seed(24) ?mydata4<- as.data.frame(matrix(sample(1:100,10*38,replace=TRUE),ncol=38)) ?dim(mydata4) #[1] 10 38 ?library(matrixStats) res<-do.call(cbind,lapply(1:400, function(i) {permutation<-sample(mydata4); (rowMeans(permutation[,1:27])-rowMeans(permutation[,28:38]))/(rowSds(permutation[,1:27])+rowSds(permutation[,28:38]))} )) ?dim(res) #[1]? 10 400 A.K.

Hello, I am trying to create parcels for a CFA model. I am trying to average 6 sets of 3 variables each into parcels. I don't understand why I am getting an error message as follows: Thanks for your help, Catherine atds1par <- rowMeans(semHW1dat1[, c("atds1", "atds2", "atds3")], na.rm=TRUE) atds2par <- rowMeans(semHW1dat1[, c("atds4",

First PRoblem solved > read.csv("KT80.csv") X x 1 1 0.01331361 > I ommitt "" in calling the file name... 2011/12/14 Trying To learn again <tryingtolearnagain@gmail.com> > Hi all, > > I have 100 csv files always with this information (I Attach two example > excels) > > KT80.csv contains: > ,"x" >

I really want to do this: abline( a=tan(-kT*pi/180), b=kY-tan(-kT*pi/180)*kX ) where kX,kY and kT are vectors of equal length. But I can't do that with abline unless I use a loop, and I haven't figured out the least unelegant way of writing the loop yet. So is there a way to do this without a loop? Or if I am to resort to the loop, what's the best way of doing it considering that I

Hello! I have a dataset like this: X1 X2 X3 X4 X5 X6 X7 X8 1 2 2 1 2 3 2 6 2 3 2 5 7 9 1 3 1 9 12 6 1 1 3 6 The columns X1-X6 contains ordinary numeric values. X7 contains the number of the first column that the rowMeans should be calculated from and X8 contains the last column

Dear List, I'm not even sure this is an issue or not, but ?rowMeans has: Value: A numeric or complex array of suitable size, or a vector if the result is one-dimensional. The ?dimnames? (or ?names? for a vector result) are taken from the original array. If there are no values in a range to be summed over (after removing missing values with ?na.rm = TRUE?), that

Hi all, I have a matrix called 'data', which looks like: > data[1:4,1:4] Probe_ID Gene_Symbol M1601 M1602 1 A_23_P105862 13CDNA73 -1.6 0.16 2 A_23_P76435 15E1.2 0.18 0.59 3 A_24_P402115 15E1.2 1.63 -0.62 4 A_32_P227764 15E1.2 -0.76 -0.42 > dim(data) [1]

I would like to calculate the mean of tree leader increment growth over 5 years (I1 through I5) where each tree is a row and each row has 5 columns. So far I have achieved this using rowMeans when all columns are numeric type and used in the calculation: Data1 <- data.frame(cbind(I1 = 3, I2 = c(0,3:1, 2:5,NA), I3 =c(1:4,NA,5:2),I4=2,I5=3)) Data1 Data1$mean_5 <- rowMeans(Data1, na.rm =T)

Hello, I have some dataset, which i read it from external file using the (data <- read.csv("my file location")) and read as a dataframe > is(data) [1] "data.frame" "list" "oldClass" "vector" but i have also converted this into a matrix and tried to apply my code but didnt work. Anyways, suppose i have the following data.

In R 3.3.3, I observe the following on Ubuntu 16.04 (when building from source as well as for the sudo apt r-base build): > x <- c(NA, NaN) > mean(x) [1] NA > mean(rev(x)) [1] NaN > rowMeans(matrix(x, nrow = 1, ncol = 2)) [1] NA > rowMeans(matrix(rev(x), nrow = 1, ncol = 2)) [1] NaN > .rowMeans(x, m = 1, n = 2) [1] NA > .rowMeans(rev(x), m = 1, n = 2) [1] NaN >

Hello: I'm reading in a series of text files (100 files that are each 2000 rows by 6 columns). I wish to combine the columns (6) of each file (100) and get the row mean. I'd like to end up with a data.frame of 2000 rows by 6 columns. foo <- list() for(i in 1:10){ # The real data are read in from a series of numbered text files foo[[i]] <- data.frame(x1 = rnorm(100), x2 =

https://bugzilla.mindrot.org/show_bug.cgi?id=2680 Bug ID: 2680 Summary: Regression in server-sig-algs offer in 7.4p1 (Deprecation of SHA1 is not being enforced) Product: Portable OpenSSH Version: 7.4p1 Hardware: Other OS: Linux Status: NEW Severity: enhancement Priority: P5

Hi all, I´m trying to use write function to save the output of a program (my constructed "H" matrix) randz<-matrix(rnorm(1000000),500,2000) H<-matrix(0,500,2000) H[1,]<-randz[1,] for (j in 1:2000){ for (i in 2:500){ if(i<251) H[i,j]<-0.6*H[i-1,j]+randz[i,j] else H[i,j]<-H[i-1,j]+randz[i,j] }} write(H, file = "datad.txt",2000) If I ommit the 2000 on

How do we specify a contrast interaction matrix for an ANOVA model? We have a two-factor, repeated measures design, with Cue Direction (2) x Brain Hemisphere(2) Each of these has 2 levels, 'left' and 'right', so it's a simple 2x2 design matrix. We have 8 subjects in each cell (a balanced design) and we want to specify the interaction contrast so that: CueLeft>CueRght

Hello, I'm having trouble in using "assign(paste ..." command . I could create several dataframes following trinomial distribution using it but it could not be used to check their row means of the created dataframe. For example, the following works: probTrt=matrix(0,4,3); probTrt; #malf, death, normal probTrt[1,]=c(0.064,0.119,0.817);#for Trt 1 probTrt[2,]=c(0.053,0.125,0.823);#for

Hi, I'm trying to fit nonlinear mixed effects model using nlme function but getting an error message. Here is what I have: fitted_model = nlme(scores~spline(b1,b2,b3,kt,time), fixed = list(b1~1, b2~1, b3~1, kt~1), random = b1+b2+b3~1, groups= ~id, data = sdat, start = c(b1=3.5,b2=2,b3=.60,kt=3.5),verbose=T) Error: Error in

On Fri, Mar 31, 2017 at 10:14 PM, Prof Brian Ripley <ripley at stats.ox.ac.uk> wrote: > From ?NA > > Numerical computations using ?NA? will normally result in ?NA?: a > possible exception is where ?NaN? is also involved, in which case > either might result. > > and ?NaN > > Computations involving ?NaN? will return ?NaN? or perhaps ?NA?: >

Hi, I am a Ph.D. student from Québec, Canada. I’m a beginner with R and Bioconductor. Until now the only experience I have is in analyzing microarray data using affy and limma packages. Now I am trying to analyze Rat Gene 10 st arrays and I would like to run RMA analysis and Smyth moderated t test on those arrays. Since no cdf official package is available for those arrays, after reading many