similar to: Replace query

Hello, I have a dataframe (tab separated file) which looks like the example below - two values separated by a comma, and tab separation between each of these. [,1] [,2] [,3] [ ,4] [1,] 0,1 1,3 40,10 0,0 [2,] 20,5 4,2 10,40 10,0 [3,] 0,11 1,2 120,10 0,0 I would like to calculate the percentage of the smallest number separated by the comma by: 1) summing the values e.g. for

Hi, I would like to replace all the max values per row with "1" and all other values with "0". If there are two max values, then "0" for both. Example: from: 2 3 0 0 200 30 0 0 2 50 0 0 3 0 0 0 0 8 8 0 to: 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 Thanks! -- View this message in context:

Hi, I'm using the hist function to plot the frequency of 21 variables, but it keeps starting the x-axis from 0 and adding variables 1 and 2 together (all other vairables have the correct frequencies). I suspect it adds 1 and 2 together so that 0 can fit in with demarcations at intervals of 5. Using "xlim=c(1,21)" to specify that i don't want to include 0 and using the

Are there any standards emerging for how to represent tables in Markdown? Regards, - Daniel -------------------------------------------- Dr Daniel Winterstein Winterwell Associates Ltd tel: 0772 5172 612 http://www.winterwell.com Registered in Scotland, company no. SC342991

Hi, I am using *Thinking Sphinx version 2.0.11 *in one of my project. To create an index I ran* **rake thinking_sphinx:index *and I got the following error Generating Configuration to /home/saidev/Ubuntu One/burgundy/ssearch/config/development.sphinx.conf rake aborted! At least one field is necessary for an index Tasks: TOP => thinking_sphinx:index (See full trace by running task with

Hello, I have an example file which can be generated using: dat <- read.table(tc <- textConnection( 'T T,G G T C NA G G A,T A A NA'), sep="") I also have a reference file with the same number of rows, for example: G C A I would like to transform the file to numerical values using the following arguments: 1) Where data points have two letters separated by a comma, e.g.

Hi, I'm trying to generate a distance matrix between sample pairs (example below). I'm not very familiar with the loop command which I expect I will need for this. The example below demosntrates what I'd like to get out of the data - essentially, to calculate the proportion of positions where two samples differ. Any help much appreciated! Also, any notes on how the functions work

Full_Name: Alexander Yephremov Version: R 2.6.2 GUI 1.23 (4932) (4932) OS: Mac OS X 10.4 Submission from: (NULL) (193.174.239.91) Hi! > array <- 0*1:50 > array [1] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 > write(array, "array.file", sep=",") This is how array.file looks: 0,0,0,0,0 0,0,0,0,0 0,0,0,0,0

Dear R users, I would like to draw map and import it in maptools/spatstat packages. The 'raw data' I have come from a web page (<map>...</map>) and are basically a list of coordinates of a polygon. I would like to know how to import them in R; I checked the maptools packages, but all the examples use existing .dbf files. I just have a (serie of) text file(s) looking like

Hi, I'm trying to assign a score to each row which allow me to identify which rows differ. In the example file below, I've used "," to indicate column separators. In this example, I'd like to identify that row 1 and row 5 are the same, and row 2 and row 4 are teh same. Any help much appreciated. Also, any comments on what the command lines do would be fantastic. Thanks!!

Hi: I have a question about the use of the survfit function after the estimation of a cox proportional hazard model with a frailty term. My goal is to estimate expected survival probabilities while controlling for the group-specific frailty term. First, I estimate a model of the following form: model1 <- coxph(Surv(t0, t, d) ~ x1 + x2 + frailty(id), na.action=na.exclude,

I am a true R novice aonly using it for this function ;) I am trying to use color2D.matplot to form a image of my data using the following conditions color2D.matplot(fi1, c(dr), c(dg), c(db), nslices=7, ylab='Species', xlab="gene", show.legend=TRUE) where fi1 is my matrix. I have a matrix with 36 columns and 130 rows. most entries are 1 or 0 and I am trying to get this

I am unfamiliar with R and I’m trying to do few statistical things like GLM and GAM with it. I hope my following questions will be clear enough: My datas ( y(i,j ))are run off triangles for example : J=1 J=2 J=3 I=1 1 2 3 I=2 4 5 I=3 6 My model is : E[y(i,j)] =m(i,j) Var[y(i,j)] =constant *m(i,j) Log(m(i,j)) = eta (i,j) eta (i,j) = c + alpha(i)

I'm developing a naive bayes in R. I have the following data and am trying to predict on returned (class). dat = data.frame(home=c(0,1,1,0,0), gender=c("M","M","F","M","F"), returned=c(0,0,1,1,0)) str(dat) dat$home <- as.factor(dat$home) dat$returned <- as.factor(dat$returned) library(e1071) m <- naiveBayes(returned ~ ., dat) m

Hello! I wont to use a function is.na() I have two vectors: > a=c(1,NA,3,3,3) > b=c(0,0,0,0,0) and when I use is.na function it's ok: > is.na(a) [1] FALSE TRUE FALSE FALSE FALSE but I would create sth like this: for i in 1:length(a){ if (wsp[i] == is.na(a)) {b=43} } or like this if(is.na(a)) b=3 else a [1] 1 NA 3 3 3 but I always get an error: the condition has

Hi all, I am sorry if this is a very basic quesion, but I have no experience with analyzing spatial data and could not find the right function/package quickly. Any hints would be much appreciated. I have a matrix of spatial point patterns like the one below and want to find the number of independent components (if that's the right term) in that matrix (or in that image). x=matrix(c(0,1,0,0,0,

Hello Folks, I have 5 columns for thousands of tree records that record whether that tree was alive or dead. I want to recode the columns such that the cell reads "found" when a live tree is first observed, "alive" for when a tree is found alive and is not just found, and "mort" when it was previously alive but is now dead. Given the following: > tree_live

Greets, I'm trying to use nlminb() to estimate the parameters of a bivariate normal sample and during one of the iterations it passes a parameter vector to the likelihood function resulting in an invalid covariance matrix that causes dmvnorm() to throw an error. Thus, it seems I need to somehow communicate to nlminb() that the final three parameters in my parameter vector are used to

Hi all, I am trying to rebuild the results of a study using a different data set. I'm using about 450 observations. The code I've written seems to work well, but I have some troubles minimizing the negative of the LogLikelyhood function using 5 free parameters. As starting values I am using the result of the paper I am rebuiling. The system.time of the calculation of the function is

hi i am creating some variables from same data, but somewhere is different rouding. look: P = abs(fft(d.zlato)/480)^2 hladane= sort(P,decreasing=T)[1:10]/480 pozicia=c(0,0,0,0,0) for (j in 1:5){ for (i in 2:239){ if (P[i]/480==hladane[2*j-1]){pozicia[j]=i-1}}} period=479/pozicia > P[2]/334 [1] 0.0001279107 > hladane[1] [1] 0.0001279107 > P[2]/334==hladane[1] [1]