similar to: Storing output vector form a loop as a matrix

Dear R users I am trying to obtain p-values for (quasi)poisson lmer models, including Markov-chain Monte Carlo sampling and the command summary. > > My problems is that p values derived from both these methods are totally different. My question is (1) there a bug in my code and > (2) How can I proceed, left with these uncertainties in the estimations of > the p-values? > > Below

Dear R users I am trying to obtain p-values for (quasi)poisson lmer models, using Markov-chain Monte Carlo sampling and the command summary. > > My problems is that p values derived from both these methods are totally different. My question is (1) there a bug in my code and > (2) How can I proceed, left with these uncertainties in the estimations of > the p-values? > > Below is

hi, first I want to say that I'm new here, and new with copula and R. That is the reason why I'm writing, if somebody can help me. I have to make an example of Copula. On internet I've found this forum and that copula can calculate with R. Can somebody help me with the thing how can I start and where can read about these stuffs. Thank to all who can help! -- View this message

Hello, I would have some details and explanations about the results I get. In fact, I start with a uniform sample between -1 and 1, and then plot its density. My problem is that the density ranges are much more longer than I expected : samp <- runif(10000,-1,1) plot(density(samp)) Instead of varying between -1 and 1, the density varies between approximaly -1.5 and 1.5 Could someone explain

Hi, please use the following the matrix z as the example: x<-c(2,4,5,7,6,9,8,2,0) y<-matrix(x,3,3) z<-apply(y,2,function(x)x/sum(x)) z On Tue, Mar 23, 2010 at 6:59 PM, David Winsemius <dwinsemius@comcast.net>wrote: > > On Mar 23, 2010, at 9:05 PM, Hongwei Dong wrote: > > Hi, R-helpers, >> >> I'm trying to use R to do a Monte Carlo simulation and

Hi all, I was unable to find a solution to my problem in the archives, but this might be due to a lack knowledge on the correct terminology on my part. Please forgive me if this has been explained before and please forgive me my probably clumsy way of explaining things. This is what I want to do: I have a list made up of 6 lists containing 7 4x4 matrices each. My goal is to select a large

Well apparently this has nothing to do with the gini() command. I cannot get it to work for something as simple as sum() Here is the little example I am playing with, maybe someone can help me find my error: a<-c("A","B","C","A","B","C","A","A","C","B")

Dear List, We are planning a genotyping study to be analyzed using false discovery rates (FDRs) (See Storey and Tibshirani PNAS 2003; 100:9440-5). I am interested in learning if there is any consensus as to how many features (ie. how many P values) need to be studied before reasonably reliable FDRs can be derived. Does anyone know of a citation where this is discussed? Bill Dupont William D.

I'd like to be able to test linear hypotheses after setting up and running a model using optim or perhaps nlm. One hypothesis I need to test are that the average of several coefficients is less than zero, so I don't believe I can use the likelihood ratio test. I can't seem to find a provision anywhere for testing linear combinations of coefficients after max. likelihood. Cheers

I want to do "moran's I test" in R language. I try to use "gearymoran" in Package "ade4","moran" in Package "spdep", and Moran.I in Package "ape". But I do not know how to do it because data format is different. My data: x y dbh 111.03 10.7 7 118.11 0.28 1.2 165.36 0.36 8.4

Hello there, would you please look into my codes? Here I have following: > set.seed(100) > samp <- sample(c(1,-1,0), 20, replace=T); samp [1] 1 1 -1 1 -1 -1 0 -1 -1 1 -1 0 1 -1 0 0 1 -1 -1 0 Here I want to calculate the length of each unique number for above vector. How can I do that? Thanks in advance [[alternative HTML version deleted]]

Dear All, I am trying to build a program which will take repeated samples without replacement from a population of values. The interesting catch is that I would like the sample values to be removed from the population, after each sample is taken. For example: pop<-c(1,5,14,7,9,12,18,19,65,54) sample(pop, 2) = lets say, (5,54) ## This is where I would like values (5, 54) to be removed from

Dear All, I am planning to run a Monte-Carlo experiment which involves to do roughly 100.000 times the following 1- Generating a sample of, say, 50.000 numbers from an ARMA or GARCH 2- Doing some regressions on the series 3- On each regression storing one special value from the results into a sequence that will be analyzed later. The experiment is calculation-intensive, and I suspect some

I have some data measured with a coarsely-quantized clock. Let's say the real data are q<- sort(rexp(100,.5)) The quantized form is floor(q), so a simple quantile plot of one against the other can be calculated using: plot(q,type="l"); points(floor(q),col="red") which of course shows the characteristic stair-step. I would like to smooth the quantized

Hi, We have recently published a paper on floating point accuracy analysis through Monte Carlo Arithmetic. We also released the open-source tool Verificarlo (https://github.com/verificarlo/verificarlo) that relies on LLVM for instrumenting floating point operations. Could you please add our paper to http://llvm.org/pubs/ ? Verificarlo: checking floating point accuracy through Monte Carlo

Dear list users, I need to learn about MCMC methods, and since there are several packages in R that deal with this subject, I want to use them. I want to buy a book (or more than one, if necessary) that satisfies the following requirements: - it teaches well MCMC methods; - it is easy to implement numerically the ideas of the book, and notation and concepts are similar to the corresponding R

Hi All, I am using canonical correspondence analysis to compare a community composition matrix to a matrix of sample spatial relationships and environmental variables. In order to parse out how much variance is explained purely by space (S/E) or the environment (E/S) I am using a conditional (partial) CCA. I want to test significance via Monte Carlo but I can not find a way to do this with a

Hello all, I would like to know what the difference is between chisq.test and fisher.test when using the Monte Carlo method with simulate.p.value=TRUE? Thank you -- View this message in context: http://r.789695.n4.nabble.com/Difference-in-Monte-Carlo-calculation-between-chisq-test-and-fisher-test-tp2322494p2322494.html Sent from the R help mailing list archive at Nabble.com.

Hi AlL, I ahve this problem that my objective function is discontinous in the paramaters and I need to use methods such as nelder-mead to get around this. My question is: How do i compute standard errors to a problem that does not have a gradient? Any literature on this is greatly appreciated. Jean,

Hi, I am facing the problem that I want to plot a histogram chart set freq to true and overlay with normal or weibull or exponential distribution curve. The sample code is shown as below: >samp<-c(-8.2262,-8.2262,-8.2262,-8.20209,-8.09294,-8.07321,-8.07321, -8.07321,-8.07175,-8.04948,-8.04948,-8.04948,-8.03848,-8.03848,