similar to: Help with significance. T-test?

#I wish to create a "list of three dataframes" ("results2") from a "list of two dataframes" (temp) and a dataframe ("c")? #Please advise. a <- data.frame(x=c(1,2,3),y=c(5,7,9)) b <- data.frame(x=c(2,4,7,9),y=c(2,3,5,4)) c <- data.frame(x=c(22,34,7,9),y=c(52,63,5,4)) results1 <- list(a,b,c) #what I want #but this is how I need to get there

Hi,there, I am using R package "boot" to bootstrap. I have one question here: does anybody possibly know how the boot package generates the "indices" which is used in the statistic function? I thought "indices = sample(data, replace=TRUE)", but when I replaced "indices" with this command and used "boot", I got different results. Specifically,

Hello, I have a ferret index with 2 fields: Acts_as_ferret :fields => [:client, :content] If I do model.find_by_contents(query) I obtain all results by the query but I would like to obtain 3 results for each client. Any ideas? Thanks for all. -- Posted via http://www.ruby-forum.com/.

I am calculating the mean of each column grouped by the variable 'id'. I do this using aggregate, data.table, and plyr. My aggregate results do not match the other two, and I am trying to figure out what is incorrect with my syntax. Any suggestions? Thanks. Here is the data. myData <- structure(list(var1 = c(31.59, 32.21, 31.78, 31.34, 31.61, 31.61, 30.59, 30.84, 30.98, 30.79, 30.79,

Dear R helpers, I have some difficulties in using ''break'' function with loop, and the followings are my script. What I try to do is (1) permute ''or'' first; (2) doing t-test if this ''or'' pass criteria 1 (k=1); (3) end the loop when I get 10 permutations; (4) redo everything again but this time use criteria 2 (k=2) (I have more criteria 1:n).

Just to inform: I posted that before in R-sig-ecology but as it might be interesting also for other useRs, I post it also to the general r-user list: Hello Alexandre, thank you very much. I also found another way to extract summarizing information from lm results over e.g. 1000 repeated model runs: results2 <- t(as.data.frame(results)) summary(results2) Although some questions popped up in

Hi together I'm pretty new to R, so excuse me if it is a basic question. I have a big dataset (extract of it found in the attachment) of returns from firms. I'd like to compute the Pearson correlation of each firm with the "Market" and the corresponding p-Value. So I thought of making a list of 'cor.test's and then extract the needed values with a for loop. What I did so

Hi, I'm trying to write a simple function like case1 <- function (m, cov, Q, R) { theta <- (acos(R/sqrt(Q^3))) beta <- (-2)*sqrt(Q)*cos(theta/3)+m[1]/3 rho1 <- (-2)*sqrt(Q)*cos((theta+2*pi)/3)+m[1]/3 rho2 <- (-2)*sqrt(Q)*cos((theta-2*pi)/3)+m[1]/3 stderrb <- deltamethod( ~(-2)*sqrt(Q)*cos(theta/3)+x1/3,m,cov) stderrr1 <- deltamethod(

Hello All, Okay i think I''m finally getting all of what i want out of ferret working, thanks mostly to reading this forum and also getting ALOT of questions answered, thanks alot everyone. Anyway my last ferret task is too get the results sorted by a field called date_registered and have this working with pagination. here is what i''m doing at the moment:

Hi, I am working on a system which automatically answers user questions (such systems are commonly called "Question Answering systems"). I evaluated different versions of the same system on a publicly available test sets. Naturally, there is a fixed number of questions in the test set, and the system answers some right and some wrong. I want to compare each version of the system

I believe this may be more related to analysis than it is to R, per se. Suppose I have the following function that I wish to integrate: ff <- function(x) pnorm((x - m)/sigma) * dnorm(x, observed, sigma) Then, given the parameters: mu <- 300 sigma <- 50 m <- 250 target <- 200 sigma_i <- 50 I can use the function integrate as: > integrate(ff, lower= -Inf, upper=target)

Hello, I have a data set which is similar to the following data mice <- rep(letters[1:4],10) outcome <- sample(c(0,1),length(mice),replace=T) group <- c(rep("A",length(mice)/2),rep("B",length(mice)/2)) my.data <- data.frame(mice,outcome,group) my.sort.data <- my.data[order(my.data[,1]),] I would like to test wether there is a different between group A and B

Martyn, you write > I don't think restart() is necessary - it just seems like an invitation to > bad programming to me. It's needed when comparing, say, the time to convergence (if at all) of various iterative processes, for each of a few hundred simulated values. For example one wants basically function(data){ summary<-rep(NA,1000) for(i in 1:1000){

Dear R-SIG-Debian, I am using R version 3.1.2 with rstudio-server 0.98.113 on debian build 3.2.0-4-amd64 #1 SMP Debian 3.2.68-1+deb7u1 x86_64 GNU/Linux. I often use the %dopar% operator in from the foreach package to run code in parallel. However, the only other use on the box seemingly installed a few items and suddenly %dopar% will use far more than the number of cores I am specifying and

I am running a simulation many times changing one parameter each time and recording the outcome. I have to produce a plot to make a sense of the bunch of numbers I get from every run. My problem is to insert a multi-line text to keep track of which result correspond to which parameter values. A legend does not work in this case because I will plot 2 variables and the corresponding experimental

Suppose we have files in one folder file1.bin, file2.bin, ... , and 1460slice(file) with dim of 720 * 360 in directory C:\\PHD\\Climate Data\\Wind\\ and we want to read them and make a loop to go from 1 to 4 and take the average, then from 4 to 8 and so on till 1460. in the end we will get 365 files . I need those 365 files to be in one new folder for later use in my model I tried using this

Hi, I've got the following code which seems to work fine for a single file if I specify the file name explicitly in the code. What I need to do is run it on all the files in the directory tested and augment the data frame I'm building to have more results columns.How can I do that? Here's the code: library(chron) # .Holidays / is.holiday / is.weekend TStoDate = function

Hi All, I'm still pretty new to using R - and I was hoping I might be able to get some advice as to how to use 'apply' or a similar function instead of using nested for loops. Right now I have a script which uses nested for loops similar to this: i <- 1 for(a in Alpha) { for (b in Beta) { for (c in Gamma) { for (d in Delta) { for (e in Epsilon) { Output[i] <-

Hello r-help, I am using the excellent np package to conduct a nonparametric kernel regression and am having some trouble plotting the results. I have 2 covariates, x1 and x2, and a continuous outcome variable y. I am conducting a nonparametric regression of y on x1 and x2. The one somewhat unusual feature of these data is that, to be included in the dataset, x1 must be at least as large as x2.

hi, at first; thanks for the help on getting confidence intervals in R. now I have a pure statistical question. I hope you don't mind if I ask ... I have an expectation of how large my beta-weight in a regression should be - so I have an "ideal" or expected regression line. Now the real beta-weight is less then the expected and when I draw the confidence interval lines