similar to: sampling vectors

Dear Listers, I emailed the list a few days ago about how to bootstrap a community matrix (species by sites) and get a consensus tree with node support. A friend pointed out that a similar question remained unanswered in 2004. I wish to re-word my question: is anyone aware of a package / method to obtain a majority-rule consensus tree from x distance matrices ? Is anyone using R to generate

Hi, I'm trying to match peaks between chromatographic runs. I'm able to match peaks when they are chromatographed with the same method, but not when there are different methods are used and spectra comes in to play. While searching I found the ALS package which should be usefull for my application, but I couldn't figure it out. I made some dummy chroms with R, which mimic my actual

Dear list members, I have a series of /unequal/ probabilities [p1,p2,...,pk], describing mutually exclusive events, and a "remainder" class with a probability p0=1-p1-p2-....-pk, and need to calculate, for a given number of trials t>=k, the combined probability that each of the classes 1...k contains at least 1 "event" (the remainder class may be empty). To me this reaks

Hi all, I have two questions 1 - I have the version 1.4.1 of R, and it doesn't have the 'agrep' function in the base library. Is there a way to make this funcion avaliable in R 1.4.1? I mean, how to 'copy' it from R 1.8.1 and 'paste' it in R 1.4.1? 2 - The AGREP function doesn't give me the Levenshtein distance (edit distance). Is there a function in R that does

Hello, i wrote this function guete and now i want to plot it: but i get this error message. i hope someone can help me. Error in dim(robj) <- c(dX, dY) : dims [product 16] do not match the length of object [1] p_11=seq(0,0.3,0.1) p_12=seq(0.1,0.4,0.1) guete = function(p_11,p_12) { set.seed(1000) S_vek=matrix(0,nrow=N,ncol=1) for(i in 1:N) { X_0=rmultinom(q-1,size=1,prob=p_0)

Dear R'ers, When I used S-plus i wrote a small program for a Mantel-Haenszel test for trend (I think it worked). Unfortunately I can't get it working in R. It appears as if my use of 'el' is the problem but I can't sort it out. Error in apply(array, c(, 2, 3), function(el) el * 1:s) : argument is missing, with no default Further down in the program I use 'el'

Dear listers, I need to export a distance matrix in the following format : a 0.0 1.0 0.2 1.0 1.0 b 1.0 0.0 1.0 1.0 1.0 c 0.2 1.0 0.0 1.0 1.0 d 1.0 1.0 1.0 0.0 1.0 e 1.0 1.0 1.0 1.0 0.0 I tried write.matrix() from the MASS library, which gives: a b c d e 0.0 1.0 0.2 1.0 1.0 1.0 0.0 1.0 1.0 1.0 0.2 1.0 0.0 1.0 1.0 1.0 1.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 0.0 Does anyone know of an R trick to change

I've had a need for multinomial "random number generation" occasionally. And other people too. The following code is currently in the (very small ``not very high importance'') CRAN package normix --- which I will rename to "nor1mix" very seen because of a ``name registration'' problem I want to add "this" (well the functionality) to a

Hola Jesús, Si no entiendo mal lo que planteas, has observado unas frecuencias N = c(12, 0, 8, 6, 4, 2) de pedidos acaecidos en 1:6 días, en total n = sum(N) pedidos. Llamemos P = (p1, p2, ?, p6) a las probabilidades ?teóricas? de pedido en cada día. En principio el vector N se puede considerar una realización de una distribución multinomial M(n; p1, ?, p6). P se puede estimar mediante las

Dear Listers, I am trying to match tables that DO NOT have the same length. The tables result from the function "table()" so they look like this: table 1 2 3 4 3 5 7 table 2 1 2 3 6 4 5 I need the following output: (NOTICE THE ZEROS) 1 2 3 4 table1 0 3 5 7 table2 6 4 5 0 Unfortunately, I was not successful using "match()". Previous postings explain how to do

Dear All, I would like to generate m positive real numbers c_i, I=1,...,m, such that (1) c_1 + c_2 + ... + c_m=m, (1) after being ordered into c_1 >= c_2 >= .... >=c_m>0, we have that c_m is of the same order of m^(-1/8), when m is sufficiently large. Thanks, -Chee [[alternative HTML version deleted]]

Dear listers, I am trying to assess variance components for a nested, mixed-effects model. I think I got an answer that make sense from R, but I have a warning message and I wanted to check that what I am looking at is actually what I need: my data are organized as transects within stations, stations within habitats, habitats within lagoons. lagoons: random, habitats: fixed the question is:

After scouring the online R resources and help pages, I still need clarification on the function rmultinomial(). I would like to create a vector, say of 100 elements, where every element in the vector can take on the value of 0, 1 or 2, and where each of those values have a specific probability. ie. the probability a given element in the vector = 0 is 0.06, 1 = 0.38, 2 = 0.56 (probabilities sum

Dear listers, a central problem in conservation biology is the selection of sites in reserve network design. many algorithms have been published, and I was wondering any have been implemented in R. I did not seen anything on CRAN or R-help, or on the web in general. Best regards, Eric Eric Pante ---------------------------------------------------------------- College of Charleston, Grice

R Help on 'chisq.test' states that "if 'simulate.p.value' is 'TRUE', the p-value is computed by Monte Carlo simulation with 'B' replicates. In the contingency table case this is done by random sampling from the set of all contingency tables with given marginals, and works only if the marginals are positive... In the

(apologies for the cross-posting, and for this being a more general stats question rather than a specific-to-R one. I assure you I will be doing the actual analysis in R :) I am trying to determine the distribution and variance for a classic stochastic (transition) matrix problem such that: let x(t) be an initial state vector consisting of counts of classes A, B and C: x(t) =

Javier, Creo que aquí aplica la ley de Linus que dice: "Dado un número suficientemente elevado de ojos, todos los errores se convierten en obvios". La persona que revisa y encuentra un error no necesariamente tiene que ser la misma que la que lo escribe. Una motivación muy importante al compartir un código es la de recibir los beneficios del control de calidad por parte de tus pares.

Hi, I'm trying to write a function that will divide a given range of numbers into 3 sets using sample(), without repetition. Currently I'm trying this approach: r <- 1:10 s1 <- sample(r,size=3) Next, I want to remove the selected elements from r and sample() from the remainder. r <- r[ -(r=s1) ] s2 <- sample(r,size=3) When I go to remove the elements contained in s2 from

Dear R-users, Is there a function in R that classifies data in more than 2 groups using logistic regression/classification? I want to compare the c-indices of earlier research (lrm, binary response variables) with new c-indices obtained from 'multiple' (more response variables) logistic regression. Best regards, Stephanie Delalieux Department Biosystems M?-BIORES Group of Geomatics

Hi everyone, I have a dataset(named "Mydata") which includes 4 different variables named; s1,s2,s3,s4 .Each variable(symptom) has 14 patients. I need to use random sampling to make, 5 different samples from my data with 5 patients in each sample. i.e. using all 4 variables I need to make 5 different samples by changing patients(with 5 patients in each sample). X8 X9 X10 X102 X110