similar to: multivariate distributions

Hi R Users, I have two vectors, x and y, of equal length representing two types of data from two studies. I would like to test if they are similar enough to use them interchangeably. No assumptions about distributions can be made (initial tests clearly show that they are not normal). Here some result: Two-sample Kolmogorov-Smirnov test data: x and y D = 0.1091, p-value < 2.2e-16 alternative

Hello, Is there a function in R with which we could find the greatest common divisor directly? Or is there a funciton, which could help us to find the remainder of a division directly? Best wishes! Thank you! Your truly, Qing -- View this message in context: http://r.789695.n4.nabble.com/greatest-common-divisor-tp2326262p2326262.html Sent from the R help mailing list archive at

Dear R helpers I am working on the Bi-variate Normal distribution probabilities. I need to double integrate the following function (actually simplified form of bivariate normal distribution) f(x, y) = exp [ - 0.549451 * (x^2 + y^2 - 0.6 * x * y) ] where 2.696 < x < 3.54 and -1.51 < y < 1.98 I need to solve something like INTEGRATE (2.696 to 3.54) dx INTEGRATE [(-1.51 to 1.98)]

I have been trying to get the lme4 package installed on Mac OS X... with no success. The Mac OS binary is not available on any CRAN, and I also can¹t install the package from old source. Has anyone found a solution to this problem? I am happy to use nlme for now, but I tend to prefer to do my mixed model analyses with lmer(). Thanks, Nicholas Griffin Center for Genome Sciences Washington

Hi! I'm trying to implement in R in an easy way the negative reflection method described in Silverman (1986) on p.31, ie I have a non-negative dataset and would like to estimate the density by applying a reflection method where the reflected points have weight -1. I thought there should be a way to evaluate the wanted kernel at the required points, in other words to calculate formula (2.16):

Hello, How do I get sub-matrix? Example, I would like to get matrix of size 3x7 from the matrix of size 4x7. Meaning that I try to exclude one row of the original matrix. Thanks -rofizah- [[alternative HTML version deleted]]

Hi Thanks for replying my question! What really interested me is that the package providing some complex form sampling, such as wishart, multinomial, dirichlet. And others for example conditional beta distribution confining the random variable in the interval (a, b). Since these concept are widely used in the baysian, I wonder whether somebody has already written this package. Thanks! Best

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Inspired by the functions that Barry Rawlingson and Dave Forrest posted for searching Rwiki and R-help archive, I've made up a function that does the search on Prof. Baron's site (Thanks to Prof. Baron's help on setting up the query string!): RSiteSearch <- function(string, restrict="Rhelp", format="long", sortby="score",

Dear List, Is there any function in R to generate multivariate F distribution with given correlation/covariance matrix? Actually, I just want to generate some 2-dimentional non-normal data sets (skewed) for low (may be around 0.3 cor coeff.) negatively and also positively correlated variables ? Thanks in advance. Anna

Dear All, Is there any function in R for computing "multivariate chi-square distribution"? How about "multivariate gamma distribution"? I appreciate any comment on this subject. Thank you, Amin Zollanvari PhD student Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX

As I have previously asked, in response to a similar question: Is this a homework problem? cheers, Rolf Turner rolf at math.unb.ca

I'm just getting started with R, having a lot of original work on modeling and exploring the simulation by MCMC. I want to simulate the prior and the posterior distribution of Dirichlet Process by MCMC. Is there anyone in NYC that might be a good tutor for me? -- Dr. P. NGOM, Facult? des Sciences et Techniques D?partement de Math?matiques et Informatique Universit? Cheikh Anta Diop Dakar -

First, my site will be down December 27-28 because of a network upgrade at Penn. It will also be down at least one day before that, while I upgrade the operating system. (And another day some time in January because of a planned power outage.) Second, I have replaced the search engine in my R site: http://finzi.psych.upenn.edu/ I am now using Namazu instead of HtDig. The direct link to the

Hello The excellent adapt package integrates over multi-dimensional hypercubes. I want to integrate over a multidimensional simplex. Has anyone implemented such a thing in R? I can transform an n-simplex to a hyperrectangle but the Jacobian is a rapidly-varying (and very lopsided) function and this is making adapt() slow. [ A \dfn{simplex} is an n-dimensional analogue of a triangle or

Dear list members, I want to draw surfaces of Dirichlet distributions with different parameter settings. My code is the following: #<begin code> a1 <- a2 <- a3 <- 2 #a2 <- .5 #a3 <- .5 x1 <- x2 <- seq(0.01, .99, by=.01) f <- function(x1, x2){ term1 <- gamma(a1+a2+a3)/(gamma(a1)*gamma(a2)*gamma(a3)) term2 <- x1^(a1-1)*x2^(a2-1)*(1-x1-x2)^(a3-1)

Hi I want to du a sensitivity analysis using Latin Hypercubes. But my parameters have to fulfill two conditions: 1) ranging from 0 to 1 2) have to sum up to 1 So far I am using the lhs package and am doing the following: library(lhs) ws <- improvedLHS(1000, 7) wsSums <- rowSums(ws) wss <- ws / wsSums but I think I can't do that, as after the normalization > min(wss) [1]

Dear Gregory R. Warnes, I'm a phd student in statistics, at the University of Milano Bicocca. I'm interested to the methods of estimate the parameters of the Dirichlet distribution. Do you have implemented an algorithm in R? If so, can you give me the script? or, in general, some helps? Best Regards Gianna --------------------------------------------------------------- Gianna Monti

Hello 'R' Users, I am very new on 'R', so excuse me if I ask something wrong. I have ASCII data and the colums of the data are looks like :- !------------------------- time,yr,mo,dy,hr,min,sec,lat,lon,ht,co2obs,sigma,co2model -- - -- !---------------------------- Each column has data value. Now I want to produce 2-d color maps, for example the plot should look like :- on

Hi: I have asked this question on Cross-Validated. So it might be a cross posting but havent received any responses to it. I am trying to see which distribution will best fit the data I am working on. The dataset is as following: Site Nausea headache Abdominal Distension 1 17 5 10 2 12