similar to: How to do an infinite sum in R

Hello R-helpers.. I want to ask about how I can sample data sets without having the infinite numbers coming out. For example, set.seed(1234) a<-rnorm(15,0,1) b<-rnorm(15,0,1) c<-rnorm(15,0,1) d<-rnorm(15,0,36) After come out with the sample, I need to do a transformation (by Hoaglin, 1985) for each data set. Actually I need to measure the skewness and kurtosis, that's why I

Hello, I am a student of Materials Engineering and I want to minister an introductory course of R at the university I study here in Brazil. I know R is a free software, but I just want to know if I do need a special authorization for doing it. The course will be totaly free and I also will not receive any money for doing it. The idea is just to show the program. -- Atenciosamente, Pedro

> x <- rnorm(1000) > h <- hist(x,plot=FALSE) > sum(h$density) [1] 2 ----------------------------- shouldn't it be 1?! > h <- hist(x,plot=FALSE, breaks=(-4:4)) > sum(h$density) [1] 1 ----------------------------- now it's 1. why?! -- Sam Steingold (http://sds.podval.org/) on Ubuntu 11.10 (oneiric) X 11.0.11004000 http://www.childpsy.net/ http://www.memritv.org

Hi, Given a positive integer N, and a real number \lambda such that 0 < \lambda < 1, I would like to generate an N by N stochastic matrix (a matrix with all the rows summing to 1), such that it has the second largest eigenvalue equal to \lambda (Note: the dominant eigenvalue of a stochastic matrix is 1). I don't care what the other eigenvalues are. The second eigenvalue is

I have some trouble to deal the value of 'NaN'. For example, > exp(1e3) [1] Inf > exp(1e3)*0 [1] NaN The correct answer should be 0 rather than NaN. I will very appreciate if anyone can share some technique to get a correct answer.

Greetings.? My wife is teaching an introductory stat class at UC Davis.? The class emphasizes the use of simulations, rather than mathematics, to get insight into statistics, and R is the mandated tool.?? A student in the class recently inquired about different approaches to sampling from a binomial distribution.? I've appended some code that exhibits the idea, the gist of which is that using

I am trying to do a power analysis to get the number of replicas per treatment. If I try to get the power it works just fine: setn=c(2,3) sdx=c(1.19,4.35) power.t.test(n = setn, delta = 13.5, sd = sdx, sig.level = 0.05,power = NULL) If I go the other way to obtain the "n" I have problems. sdx=c(1.19,4.35) pow=c(.8,.8) power.t.test(n = NULL, delta = 13.5, sd = sdx, sig.level = 0.05,

Hi, This might be me missing something painfully obvious but why does the cube root of the following produce an NaN? > (-4)^(1/3) [1] NaN > As we can see: > (-1.587401)^3 [1] -4 Thanks! Greg

I have a dataframe from an On-Board Survey with weights ("expwgt") and variables for up to 8 used lines: VEH1 through VEH8. The lines are labeled "MT-..1" through "MT-902". I want to know how many transfers there are between MT-802 and MT-901. That is, when one of them is VEHx and the other is VEHx+1 or VEHx-1 E.g. {VEH1 = MT-802 AND VEH2 = MT-901 } plus {VEH2 =

Are they the same with .RData being the newer format?? Thanks, ...Tao

(Sorry for reposting. Please delete previous msgs. Thanks!) Hi, all Here I created a data frame like mydates<- seq(as.Date("2010-05-29"), length = 43, by = "day") myvalues<-runif(43,0,1) myframe<-data.frame(dates=mydates, day=weekdays(dates), value=myvalues) dates day value 1 2010-05-29 Saturday 0.14576143 2 2010-05-30 Sunday 0.37669604

Dear all, I have an R script that uses Rcpp, and I have been trying to parallelize it using mclapply (I tried with the multicore and the parallel library) Sometimes (not always, interestingly), the CPU use for each core drops, usually so that the total over all cores reaches 100%, i.e., as fast as if using just one single core fully. I tried my code directly from within emacs, and also using a

Hi, I'm trying to user lmer function from lmerTest package because, if I understood correectly, it allows to make better inference than lmer method from lme4 package. However, whatever I do I keep getting this error: Error in lme4::lFormula(formula = mark ~ ssCount + sTime+ : rank of X = 1660 < ncol(X) = 1895 any ideas what could be a problem? thanks, Srecko [[alternative HTML

Hello r-help, I've been banging my head against the computer in an attempt to learn how to divide my matrix into segments by rows. I want to be able to return each segment as a newly named object. I've tried looking at the apply functions and creating a for loop but brain no work. Here's the basic starting objects that I believe would be needed to separate the matrix. mat <-

I am trying to create a barplot displaying the sums of 2 columns of data grouped by a variable. the data is set up like this: "city" "n" "y" <br> mon 100 200 <br> tor 209 300 <br> edm 98 87 <br> mon 20 76 <br> tor 50 96 <br> edm 62 27 <br> the resulting plot should have city as the x-axis, 2 bars per city, 1 representing

It is not generally advisable to get too fancy with stat functions in ggplot... things can easily get more complicated than ggplot is ready to handle when it comes to calculations. It is better to create data that corresponds directly to the graphical representations you are mapping them to. Read [1] for more on this philosophy. [1] H. Wickham, Tidy Data, Journal of Statistical Software,

Dear R users, I am running simulations (1000), and in my simulation I am looking at specific sums. For example, if the sum is >=4 then count this, if say <3, then don't count, if the sum=3, then generate a random number from uniform distribution, if this number is say less than 0.5, then count this sum, if greater than 0.5, then don't count. I am having trouble with introducing this

Hi all: My OS is 32bit winxp,but I wanna install 64bit R2.14.1. >From the following website,it says "You can also go back and add 64-bit components to a 32-bit install, or vice versa" http://cran.r-project.org/bin/windows/rw-FAQ.html#Can-both-32_002d-and-64_002dbit-R-be-installed-on-the-same-machine_003f Does it mean that I can install and run 64bit R2.14.1 under 32bit

In the following data.frame there are 6 columns, but 7 are written to the CSV file. install.packages("pmlr") library(pmlr) data(enzymes) write.table(enzymes, sep=",", eol="\n",file="albert.csv")

Hi, I am trying to normalize some data. First I fitted a principal curve (using the LCPM package), but now I would like to apply a transformation so that the curve becomes a "straight diagonal line" on the plot. The data used to fit the curve would then be normalized by applying the same transformation to it. A simple solution could be to apply translations only (e.g., as done after a