similar to: Probabilities for bivariate normal distribution with adapt

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.

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

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 R-list, I try to transform a mathematica script to R. #######relevant part of the Mathematica script (* p_sv *) dd = NN (DsD - DD^2); lownum = NN (L-DD)^2; upnum = NN (H-DD)^2; low = lownum/(2s^2); up = upnum/(2s^2); psv = NIntegrate[1/(s^NN) Exp[-dd/(2s^2)] (Gamma[1/2,0,up] + Gamma[1/2,0,low]),{s,sL,sH}, MinRecursion->3]; PSV = psv/Sqrt[2NN]; Print["------------- Results

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.

Dear R-list members, I have a problem with translating a mathematica script into R. The whole script is at the end of the email (with initial values for easy reproduction) and can be pasted directly into R. The problematic part (which is included below of course) is <--- Original Mathematica ---> (* p_svbar *) UiA = Ni (Dsi - 2Di A + A^2)/2; UiiA = Nii (Dsii - 2Dii A + A^2)/2; psvbar =

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

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

Hello, I am using sm.density() to find the bivariate joint PDFof events: For eg, x<-cbind(rnorm(30),rnorm(30)) den<-sm.density(x) Then I get the joint pdf from den$estimate in order to constructthe joint cumulative PDF. However, summing up all the values from den$estimateisnot equal to 1(have multipliedby the grid size). Anyone could help? Thanks. mc [[alternative HTML 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

Dear R-help, I'm using the 'optim' functions to minimise functions, and have read the documentation, but I'm still not sure how to determine sensible values to use for the 'fnscale' and 'parscale' options. If I have understood everything correctly, 'fnscale' should be used to scale the objective function, so that for example if the default is

Dear all, I have a bivariate dataset from a preliminary study. I want to do two things: (1) estimate the probability density of this bivariate distribution using some nonparametric method (kernel, spline etc); (2) sample a big dataset from this bivariate distribution for a simulation study. Is there any good method or package I can use in R for my work? I don?t want parametric models like

Am trying to do some study on bivariate binomial distribution. Anyone knows if there is package in R that I can use to calculate the density function of bivariate binomial distribution and to generate random samples of it. Thanks, -- View this message in context: http://n4.nabble.com/How-to-calculate-density-function-of-Bivariate-binomial-distribution-tp992002p992002.html Sent from the R help

Any one know is there any package or function to generate bivariate exponential distribution? I gusee there should be three parameters, two rate parameters and one correlation parameter. I just did not find any function available on R. Any suggestion is appreciated. -- View this message in context:

Hello all!!! 1) I am wondering is there a way to generate random numbers in R for Bivariate Uniform distribution? 2) Does R have  built-in function for generating random numbers for any given bivariate distribution. Any help would be greatly appreciated !! Good day! Haneef Anver [[alternative HTML version deleted]]

x <- iris$Sepal.Length[1:50]/iris$Sepal.Width[1:50] y <- iris$Petal.Length[1:50]/iris$Petal.Width[1:50] I want to check whether (x,y) follows a bivariate normal distribution or not, using density plot or scatter plot. Is it possible to plot a bivariate density in R. I cant find any. Arindam Fadikar M.Stat Indian Statistical Institute. New Delhi, India [[alternative HTML version

Hello, I'm quite new with R and so I would like to know if there is a command to calculate an integral. In particular I simulated a bivariate normal distribution using these simple lines: rbivnorm <- function(n, # sample size mux, # expected value of x muy, # expected value of Y sigmax, # standard deviation of

Hello, I have used the univariate Ripley K function in R, but does anyone know if there is a bivariate function built in? I have two species that I am dealing with. Also, how might I add error bars into the graphs (univariate and/or bivariate)? Thank you, Karin Leiderman k_leiderman at hotmail.com Graduate Student/Research Assistant Department of Mathematics Univesity of New Mexico

Hi, I woul like to know if it is possible to have a "R code" to generate EM Algorithm for a normal bivariate mixture. Best regard, S.F.

Hi.., is there a function in R to fit bivariate splines ? I came across 'polymars' (POLSPLINE) and 'mars' (mda) packages. Are these the one to use or are there other specific commands? Thanks. Harsh