similar to: matrix manipulation problem

Dear R-users, Say that I have a sequence of zeroes and ones: x <- c(1,1,1,0,0,0,0,1,1,1,0,0,0,0,1,1,1,0,0,0,0) The sequences of ones represent segments and I want to report the starting and endpoints of these segments. For example, in 'x', the first segment starts at location 1 and ends at 3, and the second segment starts at location 8 and ends at location 10. Is there an efficient

Hi all, I was hoping somebody may know of a function for simulating a large binary sequence (length >10 million) using a (1st order) markov model with known (2x2) transition matrix. It needs to be reasonably fast. I have tried the following; mc<-function(sq,P){ s<-c() x<-row.names(P) n<-length(sq) p1<-sum(sq)/n s[1] <- rbinom(1,1,p1); for ( i in 2:n){ s[i]

Frede Aakmann T?gersen wrote: > Perhaps > > http://stinet.dtic.mil/cgi-bin/GetTRDoc?AD=ADA266969&Location=U2&doc=GetTRDoc.pdf > > is something that you can use? Thanks a lot - that might help. Rainer > > > > Best regards > > Frede Aakmann T?gersen > Scientist > > > UNIVERSITY OF AARHUS > Faculty of Agricultural Sciences > Dept.

Hi I have two vectors, prob and size, and I want to add the random deviates of these two, i.e. sum( sapply( 1:length(prob), function(n){ rbinom(1, size(n), prob(n) } ) ) My problem is that I have to do this for a large number of value combinations. Is there a faster way of doing this? Rainer

Greetings, I have a seemingly simple task which I have not been able to solve today. I want to construct a symmetric matrix of arbtriray size w/o using loops. The following I thought would do it: p <- 6 Rmat <- diag(p) dat.cor <- rnorm(p*(p-1)/2) Rmat[outer(1:p, 1:p, "<")] <- Rmat[outer(1:p, 1:p, ">")] <- dat.cor However, the problem is that the matrix

I am looking for an efficient way to solve the following problem. I have a large matrix of continuous values with a small proportion of missing values. Columns correspond to variables where each variable has two measurements, call them A and B. The matrix is such that the columns are in sequence with respect to the variables. I would like to sum up the two measurements for each variable and each

I have a matrix of frequency counts from 0-160. x<-as.matrix(c(0,1,0,0,1,0,0,0,1,0,0,0,0,1)) I would like to apply a function creating a new column (x[,2])containing values equal to: a) log(x[m,1]) if x[m,1] > 0; and b) for all x[m,1]= 0, log(next x[m,1] > 0 / count of preceding zero values +1) for example, x[1,2] should equal log(x[2,1]/2) = log(1/2) = -0.6931472 whereas x[3,2] should

I am doing cluster analysis [hclust(Dist, method="average")] on data that potentially contains redundant objects. As expected, the inclusion of redundant objects affects the clustering result, i.e., the data a1, = a2, = a3, b, c, d, e1, = e2 is likely to cluster differently from the same data without the redundancy, i.e., a1, b, c, d, e1. This is apparent when the outcome is visualized

Dear all, Could someone point me to a function or algorithm to generate random bivariate binomial data? Some details about what I'm trying to do. I have a dataset of trees who were categorised as not damaged or damaged. Each tree is measured twice (once in two consecutive years). The trees can recover from the damage but the data is clearly correlated. As a (un)damaged tree is more likely

I have two questions for the group. One is very concrete, and is dangerously close to a "please do my homework" posting. The second follows from the first one but is more general. I would welcome the advice of experienced R users. As for the first one: I have a data frame with two variables X Y A, chris D, chris B, chris B, chris C, andrew E, andrew C, andrew B, beth

Hi the list, unlist respect the all the atomic type except orderd (it change of ordered into factor) : ### integer class(unlist(list(1:5,1:3))) #[1] "integer" ### numeric class(unlist(list(1.2,3.5))) #[1] "numeric" ### character class(unlist(list("e","e"))) #[1] "character" ### factor

Hi, I am trying to reproduce some functionalities of Excel pivot table in R, sadly, I couldn't figure out how to do it. I am wondering if this is even possible in R. Does anyone know? Here is an example: year=rep(2003,16) quarter=rep(1:4,each=4) sales=1:16 company=rep(c("a","b","c","d"),4) df=data.frame(year,quarter,sales,company) #this is the

Hi R-Users, I have a data frame containing year, month, day, and code columns. The code column is a unique character of set ('E','A','B') - I am trying to determine an efficient way of summarizing the count of each of these codes by month and year without having to use for...loops and subsets. Does anyone have any suggestions? Thanks in advance, Dave Here is a snapshot

Using R version 2.4.1 (2006-12-18) on Windows, I have a dataset which resembles this: id att1 att2 att3 1 1 1 0 2 1 0 0 3 0 1 1 4 1 1 1 ratings <- data.frame(id = c(1,2,3,4), att1 = c(1,1,0,1), att2 = c(1,0,0,1), att3 = c(0,1,1,1)) I would like to get a cross tab of counts of co-ocurrence, which might resemble this:

I have a dataframe with the following variables: idnum area gender race etc. I would like to make a table that looks like area gender race M F B W A 1 4 5 3 5 1 2 6 7 4 6 3 etc. Basically, I want to make a single broad table with a number of sub-set tables. I have tried: cbind(table(area, gender), table(area, race)) But, when I do this, I lose the labels gender / race. This makes it

Hi fellow R-users, Are there any text editors that recognize sweave (.rnw) files? I am running Windows Vista and in the past I used Tinn-R for R files but it (surprisingly) doesn't recognize rnw files and does not do any syntax highlighting for them. Thanks in advance, Greg __________________________________________________________________ Make your browsing faster, safer, and

Hi all, I was wondering whether it is possible to use the lapply() function to alter the value of the input, something in the spirit of : a1<-runif(100) a2<-function(i){ a1[i]<-a1[i-1]*a1[i];a1[i] } a3<-lapply(2:100,a2) Something akin to a for() loop, but using the lapply() infrastructure. I haven't been able to get rapply() to do this. The reason is that the "real"

Dear R People: Here is a little section of a data frame: > zzz[1:10,] DATE GENDER AGE Co DEATH1 3945 2009-04-16 M 24 Botulinic 23 3851 2009-04-16 M 35 Constitutional 23 8495 2009-04-16 F 49 Constitutional 27 10967 2009-04-16 F 47 Constitutional 28 11164 2009-04-16 F 26 Constitutional 28 15220

Hi there, I run two regressions: y = a1 + b1 * x + e1 y = a2 + b2 * z + e2 I want to test against the null hypothesis: b1 = b2. How do I design the test? I think I can add two equations together and divide both sides by 2: y = 0.5*(a1+a2) + 0.5*b1 * x + 0.5*b2 * z + e3, where e3 = 0.5*(e1 + e2). or just y = a3 + 0.5*b1 * x + 0.5*b2 * z + e3 If I run this new regression, I can test against

Hi, When qqnorm on a vector of length 10M+ I get a huge pdf file which cannot be loaded by acroread or evince. Any suggestions? (apart from sampling the data). Thanks. -- Sam Steingold (http://sds.podval.org/) on Ubuntu 11.10 (oneiric) X 11.0.11004000 http://mideasttruth.com http://honestreporting.com http://camera.org http://openvotingconsortium.org http://pmw.org.il