similar to: Error: "subscript out of bounds"

Hi everyone, > does any one knows how can I calculate mean for different samples > i.e. I have a data like this: > > s1 s2 s3 s4 > 1 0 0 0 1 > 2 1 0 1 0 > 3 0 0 0 0 > 4 0 0 0 0 > 5 0 1 0 1 > 6 1 0 0 0 > 7 0 0 0 0 > 8 0 0 0 0 > 9 0 0 0 0 > 10 0 0 0 1 > > I need to make 5 different sample with 5

I'm pasting below a working R file featuring a function I'd like to polish up. I'm teaching regression this semester and every time I come to something that is very difficult to explain in class, I try to simplify it by writing an R function (eventually into my package "rockchalk"). Students have a difficult time with predict and newdata objects, so right now I'm

Hi everyone, I have a question about functions. I have two functions: Sampling=function(fname,Total,nSample,nPatient){......return(list(Gmean,Gsd))} Power=function(alfa,m1,m2,s1,s2,n1,n2){....return(powe)} I want to use "Gmean" and "Gsd" which are the returned values from "Sampling" function, in "Power" function. i.e. when I call "power" I want

Hi, I am new to R for solving optimization problems, I have set of communication channels with limited capacity with two types of costs, fixed and variable cost. Each channel has expected gain for a single communication. I want to determine optimal number of communications for each channel maximizing ROI)return on investment) with overall budget as constraint.60000 is the budget allocated.

Hi, Using S=1000 and simdata <- replicate(S, generate(3000)) #If you want both "m1" and "m0" #here the missing values are 0 res1<-sapply(seq_len(ncol(simdata.psm1)),function(i) {x1<-merge(simdata.psm0[,i],simdata.psm1[,i],all=TRUE); x1[is.na(x1)]<-0; x1}) res1[,997:1000] #????? [,1]???????? [,2]???????? [,3]???????? [,4]??????? #x1??? Numeric,3000 Numeric,3000

Hi, i'm using this lines of code: dodge <-position_dodge(width=0.9) ggplot(dfm,aes(x = X,y = value)) + geom_bar(aes(fill = variable), position=dodge, stat="identity") + geom_errorbar(aes(ymin=value-er, ymax=value+er),width=0.25, position=dodge,stat="identity") to plot this data frame X variable value er 1 A X4 58.74 9.44 2 B X4

Hi, You might need to check library(boot).? I have never used that before.? So, I can't comment much.? It is better to post on R-help list.? I had seen your postings on Nabble in the past.? Unfortunately those postings were not accepted in R-help.? You have to directly post at ? r-help at r-project.org after registering at: https://stat.ethz.ch/mailman/listinfo/r-help ?

I'm using specify.model for the sem package. I can't figure out how to represent the residual errors for the observed variables for a CFA model. (Once I get this working I need to add some further constraints.) Here is what I've tried: model.sa <- specify.model() F1 -> X1,l11, NA F1 -> X2,l21, NA F1 -> X3,l31, NA F1 -> X4,l41, NA F1 -> X5, NA, 0.20

I have a sparse contingency table (most cells are 0): > xtabs(~.,data[,idx:(idx+4)]) , , x3 = 1, x4 = 1, x5 = 1 x2 x1 1 2 3 1 0 0 31 2 0 0 112 3 0 0 94 , , x3 = 2, x4 = 1, x5 = 1 x2 x1 1 2 3 1 0 0 0 2 0 0 0 3 0 0 0 , , x3 = 3, x4 = 1, x5 = 1 x2 x1 1 2 3 1 0 0 0 2 0 0 0 3 0 0 0 , , x3 = 1, x4

Dear All, I have got the limits for removing extreme values for each variables using following function . f=function(x){quantile(x, c(0.25, 0.75),na.rm = TRUE) - matrix(IQR(x,na.rm = TRUE) * c(1.5), nrow = 1) %*% c(-1, 1)} #Example: n <- 100 x1 <- runif(n) x2 <- runif(n) x3 <- x1 + x2 + runif(n)/10 x4 <- x1 + x2 + x3 + runif(n)/10 x5 <-

Hi everyone, I have dataset which I take random samples of it 5 times. each time I get the mean for rows for each sample. at the end I need to calculate the Average of all means for each sample and each row. to clear it up I give an example: say this is my dataset. X8 X9X10X12 X13 X14 X15 X16X17X18X19 X20 X21 X22 s1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 s2 0 0 0

Dette er en melding med flere deler i MIME-format. --=_alternative 004613C000257091_= Content-Type: text/plain; charset="US-ASCII" And some more informastion I forgot. R does not crash if I write out the formula: set.seed(123) x1 <- runif(1000) x2 <- runif(1000) x3 <- runif(1000) x4 <- runif(1000) x5 <- runif(1000) x6 <- runif(1000) x7 <- runif(1000) x8 <-

Hi Phil Here it is: [root at totorbex ~]# lspci -nn .00:00.0 Host bridge [0600]: Intel Corporation Atom/Celeron/Pentium Processor x5-E8000/J3xxx/N3xxx Series SoC Transaction Register [8086:2280] (rev 21) 00:02.0 VGA compatible controller [0300]: Intel Corporation Atom/Celeron/Pentium Processor x5-E8000/J3xxx/N3xxx Integrated Graphics Controller [8086:22b1] (rev 21) 00:10.0 SD Host controller

Hi everyone, I have a dataset(named "Mydata") which includes 4 different variables named; s1,s2,s3,s4 .Each variable(symptom) has 14 patients. I need to use random sampling to make, 5 different samples from my data with 5 patients in each sample. i.e. using all 4 variables I need to make 5 different samples by changing patients(with 5 patients in each sample). X8 X9 X10 X102 X110

Hi guys, I need to insert a row to a matrix in a for loop. I have matrix named "Avg" which is a 5x4 matrix of zeros. I have a file named "A"(4 rows,14 columns) which I make a sample of it 5 times. each time I get the mean for each column and put the result in the "Avg" matrix. this is my code: Avg=matrix(0,5,4) > > for(i in 1:5){ + res=(A[sample(nrow(A),

Hello, I have three datasets StartSignals, MainData, StopSignals and need to compound the data for each variable in MainData over dates that fall between the Start and Stop signals. (Stop signals are common and the same to all X1:X5 variables). Please see sample below: The one way I was thinking of doing this project was to setup a nested "FOR" loop and go through the three data

Dear all,   I did ANOVA for many response variables (Var1, Var2, ....Var75000), and i got the result of p-value like below. Now, I want to select those predictors, which have pvalue less than or equal to 0.05 for each response variable. For example, X1, X2, X3, X4, X5 and X6 in case of Var1, and similarly, X1, X2.......X5 in case of Var2, only X1 in case of Var3 and none of the predictors in case

Hello I have data like this x1 x2 x3 x4 x5 I want to create a matrix similar to a correlation matrix, but with the difference between the two values, like this x1 x2 x3 x4 x5 x1 x2-x1 x3-x1 x4-x1 x5-x1 x2 x3-x2 x4-x2 x5-x2 x3 x4-x3 x5-x3 x4 x5-x4 x5 Then I

Dear R-users I have a probelm running stepAIC in R1.7.1 I wrote a program which used stepAIC as a part of it, and it worked fine while I was using the previous version of R1.7.0. However, I found the program did not work any more. Now, R produces a message which tells "Error in as.data.frame.default(data) : can't coerce function into a data.frame" every time I run the part of

When data contains both factor and numeric variables, how to get quartiles for all numeric variables? n <- 100 x1 <- runif(n) x2 <- runif(n) x3 <- x1 + x2 + runif(n)/10 x4 <- x1 + x2 + x3 + runif(n)/10 x5 <- factor(sample(c('a','b','c'),n,replace=TRUE)) x6 <- factor(1*(x5=='a' | x5=='c')) data1 <- cbind(x1,x2,x3,x4,x5,x6) data