similar to: Bivariate normal

Dear list members I need a function that calculates the bivariate normal distribution for each observation. It is part of a likelihood function and I have 1000's of cases. As I understand it I cannot use packages like "mvtnorm" because it requres a covariance matrix of the same dimension as the number of observations. Basically what I need is a function that takes as arguments a

sorry for cross-posting Dear all, I have tow (several) bivariate distributions with a known mean and variance-covariance structure (hence a known density function) that I would like to compare in order to get an intersect that tells me something about "how different" these distributions are (as t-statistics for univariate distributions). In order to visualize what I mean hear a little

Dear R-List: I`m trying to calculate the probabilities for a bivariate normal distribution while using the mvtnorm-package(dmvnorm) and the adapt-package for multidimensional integration. The problem is that I can`t specify the upper bound in the adapt-package the way I need it because I don`t need a rectangular area. I want to calculate the probability starting at the origin under the line y=x.

hello, I'm trying to improve the speed of my calculation but didn't get to a satisfying result. It's about the numerical Integration of a bivariate normal distribution. The code I'm currently using x <- qnorm(seq(.Machine$double.xmin,c(1-2*.Machine$double.eps),by=0.01), mean=0,sd=1) rho <- 0.5 integral <- function(rho,x1){

HI Every one Could some one provide me definitions of following bivariate distributions gamma, exponencial, Weibull, half-normal , Rayleigh, Erlang,chi-square thanks A.S. Qureshi

Hello, Is it possible to draw level lines on the surface of a bivariate function? In the following example, to draw surface and levels lines for a multivariate normal law, I use persp, trans3d, contourLines and lines, but if the lines are correctly drawn, some parts of them are, of course, visible even if they are drawn on a non visible "face". Any suggestion to avoid this problem

Dear All, I am trying to convert some S-plus code that I have to run MCMC into R-code. The program works in S-plus, but runs slowly. I have managed to source the program into R. R recognizes that the program is there; for example, it will display the code when I type the function name at the prompt. However, the program will not run. When I try to run the program, I get the following error

Dear R-help, I first thought that the empty set (for a vector) would be NULL. x <- c() x However, the documentation seems to make clear that there _many_ empty sets depending on the vector's mode, namely, numeric(0), character(0), logical(0), etc. This is borne out by y <- letters[1:3] z <- letters[4:6] intersect(y,z) which, of course, is non-NULL: is.null(character(0)) #

hello I work on the probabilities of bivariate normal distribution. I need integrate  the following function. f (x, y) = exp [- (x ^ 2 + y ^ 2 + x * y)] with - ∞ ≤ x ≤ 7.44 and - ∞ ≤ y ≤ 1.44   , either software R or  matlab Version R 2009a Thank you for helping me Regards Mezouara hicham PhD in Metrology Hicham_dess @ yahoo.fr [[alternative HTML version deleted]]

Dear R users, I would like to plot the bivariate density surface with its marginal densities on the sides of the 3D box, just like in the picture I attach. I tried to found information about how to do it but did not find anything. Does anyone know how to do it? Thanks in advance, Eduardo.

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

Dear R-devel, Please see the recent thread on R-help, "Odd Behavior Out of setdiff(...) - addition of duplicate entries is not identified" posted by Jason Rupert. I gave an answer, then read David Winsemius' answer, and then did some follow-up investigation. I would like to change my answer. My current version of setdiff() is acting in a way that I do not understand, and a way

Dear R-devel, Please see the recent thread on R-help, "Odd Behavior Out of setdiff(...) - addition of duplicate entries is not identified" posted by Jason Rupert. I gave an answer, then read David Winsemius' answer, and then did some follow-up investigation. I would like to change my answer. My current version of setdiff() is acting in a way that I do not understand, and a way

I have the following function, a MSE calc based on some Multivariate normals: MV.MSE<-function(n,EP,X,S){ (dmvnorm(X,mean=rep(0,2),I+S+EP)-dmvnorm(X,mean=rep(0,2),I+S))^2 + 1/n*(dmvnorm(X,mean=rep(0,2),1+S+EP/2)*det(4*pi*EP)^-.5- (dmvnorm(X,mean=rep(0,2),I+S+EP ))^2)} I can get the MV.MSE for given values of the function e.g

I think I am using the improved version of setdiff(...) that handles data.frames, so I think some odd behavior was expected but this one is escaping me. It appears that the the addition of duplicate entries is not caught by the setdiff(...). Is this expected behavior? If so, is there another method or approach that should be used to identify duplicate row entries between two different data

Hello, I have been interested in setdiff() for data frames that operates row-wise. I looked in the documentation, mailing lists, etc., and didn't find exactly the right thing. Given data frames A, B with the same columns, the goal is to extract the rows that are in A, but not in B. Of course, one can usually do setdiff(rownames(A), rownames(B)) but that is cheating. :-) I played around a

Suppose F(x, y; rho) is the cdf of a bivariate normal distribution, with standardized marginals and correlation parameter rho. For any fixed x and y, I wonder if F(x, y; rho) is a monotone increasing function of rho, i.e., there is a 1 to 1 map from rho to F(x, y; rho). I explored it using the function pmvnorm in package mvtnorm with different x and y. The plot suggests the statement may be true.

Dear R-help, Suppose I write a script that looks something like this: #### script.R set.seed(something) x <- rnorm(100) y <- runif(500) # bunch of other stuff save.image() ### end of script.R Now, I give you a copy of my script.R (with the set.seed statement removed, of course) together with the .RData file that was generated by the save.image() command. Question: 1) can you tell

Dear R community, I was trying to estimate density at point zero of a multivariate distribution (9 dimensions) and for this I was using a multinormal approximation and the function dmvnorm , gtools package. To have a sense of the error I tried to look the mismatch between a unidimensional version of my distribution and estimate density at point zero with function density, dmvnorm and dnorm. At

I am experiencing strange results using dmvnorm. I define a scaled distance matrix from the coordinates bellow and then calculate a covariance matrix using a spherical correlation function. Then with certain combinations of range and sill parameters dmvnorm is returning values greater than 1. Surely the results of dmvnorm should be in the interval 0:1 (or do I just nead a holiday?). In addition