similar to: comparison of bivariate normal distributions

Hi, I'm using the package quadprog to solve the following quadratic programming problem. I want to minimize the function (b_1-b_2)^2+(b_3-b_4)^2 by the following constraints b_i, i=1,...,4: b_1+b_3=1 b_2+b_4=1 0.1<=b_1<=0.2 0.2<=b_2<=0.4 0.8<=b_3<=0.9 0.6<=b_4<=0.8 In my opinion the solution should be b_1=b_2=0.2 und b_3=b_4=0.8. Unfortunately R doesn't find

Package mvtnorm provides dmvnorm, pmvnorm that can be used to compute Pr(X=x,Y=y) and Pr(X<x,Y<y) for a bivariate normal. Are there functions that would compute Pr(X<x,Y=y)? I'm currently using "integrate" with dmvnorm but it is too slow.

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, 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 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

Hi all, I have been looking for means of add a contour around some points in a scatterplot as a means of representing the center of density for of the data. I'm imagining something like a 95% confidence estimate drawn around the data. So far I have found some code for drawing polygons around the data. These look nice, but in some cases the polygons are strongly influenced by outlying points.

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

Summary: + I am writing an R extension that needs to call dmvnorm more than 10,000 times during a model fitting computation. + My extension uses openmp for parallel execution. + As of R 3.0, it is no longer permitted for threads to call the R interpreter because there is a stack overflow check that always trips because the thread's stack is different from what R is expecting. +

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

Hello, everyone, I have a question about integration of product of two densities. Here is the sample code; however the mean of first density is a function of another random variable, which is to be integrated. ## f=function(x) {dmvnorm(c(0.6, 0.8), mean=c(0.75, 0.75/x))*dnorm(x, mean=0.6, sd=0.15)} integrate(f, lower=-Inf, upper=Inf) ## error message Error in dmvnorm(c(0.6, 0.8), mean = c(0.75,

I am using curve3d in the emdbook package to graph a gaussian copula density function generated via the copula package. Unfortunately, it appears that emdbook masks dmvnorm from the package mvtnorm in a way that prohibits copula from generating the gaussian copula. (Sounds very confusing!) For example, > library(copula) > f<-function(x,y) dcopula(normalCopula(0),c(x,y)) >

Hi there. I am receiving an unexpected error message when creating a new distribution for the survreg() function in the survival package. I understand the survival.distributions() function and have been following the Cauchy example provided in the help file. My goal is to use survreg to fit a gamma distribution to interval censored data. Here is a simple example of what I'm trying to do.

Hi All, Why would calls to dnorm and dmvnorm return values that are above 1? For example, > dnorm(0.00003,mean=0, sd=0.1) [1] 3.989423 This is happening on two different installations of R that I have. Thank you. Hailu [[alternative HTML version deleted]]

Hi, All: Is there a way to identify whether any users are using a particular package in a shared network R installation? I ask, because we have such a multiple-user installation and when I tried to install a package using Rgui that was in use by Rterm on a single-user installation, 'install.packages' deleted the existing package but failed to install the new version;

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

Are there any functions in R for fitting distributions? In particular, I would like to fit the weibull and extreme-value distributions when: i) the data are given and the maximum likelihood estimates are required; ii) the sample moments are available but the complete data record is not (so moment estimates are required). Any suggestions will be gratefully received.

Dear R users, i try to use function dmvnorm(x, mean, sigma, log=FALSE) from R package mvtnorm to calculate the probability of x under the multivariate normal distribution with mean equal to mean and covariance matrix sigma. I become the following Error in solve.default(cov, ...) : system is computationally singular: reciprocal condition number = 1.81093e-19 What could be the reason of it?

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.

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