Re: [R] number of warnings

Sorry, I did not understand. What does it mean " call 999" ? -- View this message in context: http://r.789695.n4.nabble.com/number-of-warnings-tp4550325p4551999.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org maili

Re: [R] number of warnings

This is my wrong, I am so sorry for this. I just wanted to ask something which I did not know. Thanks for answer. Regards Helin. -- View this message in context: http://r.789695.n4.nabble.com/number-of-warnings-tp4550325p4552240.html Sent from the R help mailing list archive at Nabble.com. __

Re: [R] number of warnings

Any help ? -- View this message in context: http://r.789695.n4.nabble.com/number-of-warnings-tp4550325p4551760.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-he

Re: [R] indexing??

Thanks, Dear Petr Savick. Your help is enough to solve my problem. With your help I've dealt with the problem. Many thanks for your effort, Sincerely, Helin -- View this message in context: http://r.789695.n4.nabble.com/indexing-tp4428210p4431168.html Sent from the R help mailing list archiv

Re: [R] indexing??

Dear Petr Savicky, Actually, this is based on jackknife after bootstrap algorithm. In summary, I have a data set, and I want to compute some values by using this algorithm. Firstly, using bootstrap, I create some bootstrap re-samples. This step O.K. Then, for each data point within these re-samp

Re: [R] indexing??

Dear Petr Pikal and Petr Savicky thank you for your replies.. If the y vector contains different elements my algorithm gives this result; y <- c(1,2,3,4,5,6,7,8,9,10) x <- c(1,0,0,1,1,0,0,1,1,0) n <- length(x) t <- matrix(cbind(y,x), ncol=2) z = x+y for(j in 1:length(x)) { out <- vector(

[R] indexing??

Hello All, My algorithm as follows; y <- c(1,1,1,0,0,1,0,1,0,0) x <- c(1,0,0,1,1,0,0,1,1,0) n <- length(x) t <- matrix(cbind(y,x), ncol=2) z = x+y for(j in 1:length(x)) { out <- vector("list", ) for(i in 1:10) { t.s <- t[sample(n,n,replace=T),] y.s <- t.s[,1] x.s <- t.s[,2] z.s <- y.s+x.s

Re: [R] influence.measures()

Hi again, I studied with influence measures of logistic regression of some data by using R and SPSS and I get different values of DFFITS and Cook's Distance from SPSS and R outpus, but the coefficients, model formulas and leverage values are the same. Can anyone help me about ; Which is the true

[R] influence.measures()

Hi dear all, I'm wondering about the question that; Does the influence.measures(model) for linear models valid for general linear models such as logistic regression models? That is; If I fit the model like model <- glm( y~X1+X2, family=binomial) Then, if i apply the function "influence.measur

Re: [R] Deleting the last value of a vector

if you have a vector like as follows; r=c(1,2,3,4,5) then use r2=r[1:length(r)-1] -- View this message in context: http://r.789695.n4.nabble.com/Deleting-the-last-value-of-a-vector-tp3456363p3456388.html Sent from the R help mailing list archive at Nabble.com. ___

Re: [R] Repeating a function

Hi, try this; output <- list() times <- 1000 drift <-function(p0=0.4,N=40,ngen=55){ p = p0 for( i in 1:ngen){ p = rbinom(1,2*N,p)/(2*N) } return( p ) } for(i in 1:times){ result <- drift(0.4, 40, 55) output <- c(output, list(resu

Re: [R] Counting elements in columns

Hi, try this; sum(sapply(a, function(x) (x==b))) -- View this message in context: http://r.789695.n4.nabble.com/Re-Counting-elements-in-columns-tp3454930p3454936.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mai

Re: [R] if else statements in data frame

Hi ozgrerg, I am not a "good" R user, but according to me you can do this; data <- data.frame(x=c("A","A","B","A"), y=c("A","B","B","B")) for (i in 1:nrow(data)){ if(data$x[i]=="B"||data$y[i]=="B") z[i]=c("B") else z[i]=c("NA") } cbind(data,z) -- View this message in context: http://r.789695.n

Re: [R] Comparison of the amount of computation

Dear Pert, Many thanks to your reply. Fully you are right! Best wishes, Helin. -- View this message in context: http://r.789695.n4.nabble.com/Comparison-of-the-amount-of-computation-tp3448436p3449722.html Sent from the R help mailing list archive at Nabble.com. ___

Re: [R] Comparison of the amount of computation

Hi Petr, Your idea looks like logically. So, can we say this with your idea; the expected number of computation in unique(sample(...)) is fewer than sample(...). Because, the expected length is 63.39677 in unique case, while the expected length is 100 in non-unique case ? Thanks for reply, Helin

[R] Comparison of the amount of computation

Hi dear list, I want to compare the amount of computation of two functions. For example, by using this algorithm; data <- rnorm(n=100, mean=10, sd=3) output1 <- list () for(i in 1:100) { data1 <- sample(100, 100, replace = TRUE) statistic1 <- mean(data1) output1 <- c(output1, list(statistic1)) }