search for: bivariant

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

Hi: I am using the package "KernSmooth" to do the local polynomial regression. However, it seems the function "locpoly" can only deal with univariate covaraite. I wonder is there any kernel smoothing package in R can deal with bivariate covariates? I also checked the package "lcofit" in which function "lcofit" can indeed deal with bivariate case. The

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 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

Dear list I have a vector of values that allegedly have a bivariate normal distribution. I want to create a plot that shows the values I have obtained, and the bivariate normal distribution curve for the data. Is there a way of doing this in R? Many thanks for your help, Sarah. --------------------------------- [[alternative HTML version deleted]]

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]]

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:

Respected R Users, I looking for help with generating theoretical confidence regions for any of non-symmetric bivariate statistical distributions (bivariate Chi-squared distribution<Wishart distribution>, bivariate F-distribution, or any of the others). I want to to used it as a benchmark to compare a few strategies constructing confidence regions for non-symmetric bivariate data. There is

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

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 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

Hi, I'm dealing with wind data and I'd like to model their distribution in order to simulate data to fill-in missing values. Wind direction are typically following a vonmises distribution and wind speeds follow a weibull distribution. I'd like to build a joint distribution of directions and speeds as a VonMises-Weibull bivariate distribution. First is this a stupid question? I'm

This might not be the correct forum for this question for there might be some flaws in my logic so the R function I'm looking for might not be the correct, but I know there?s a lot of smart people in this forum so please correct me if I'm wrong. I have been googling and searching in this forum for something useful but so far I'm out of luck. This is the background to my problem. I

Is there code for bivariate kernel density estimation? For bivariate kernels there is kde2d in MASS kde2d.g in GRASS KernSur in GenKern (list probably incomplete) but none of them seems to accept a weight parameter (like density does since R 2.2.0) -- Erich Neuwirth, University of Vienna Faculty of Computer Science Computer Supported Didactics Working Group Visit our SunSITE at

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.., 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

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.

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 all, Given a matrix A, say, I would like to apply a bivariate function to each combination of its colums. That is if myfun<-function(x,y)cor(x,y) #computes simple correlation of two vectors x and y then the results should be something similar to cor(A). I tried with mapply, outer,...but without success Can anybody help me? many thanks in advance, vito

Dear all R gurus, My question is related to statistics rather directly to R. Suppose (X,Y) has a bivariate normal distrubution. I want to find two values of X and Y say x, and y respectively, such that: P[X<x, Y<y] = 0.05 My questions are : 1. Can x and y be uniquely found? 2. If it is, how I can find them using R Your help will be highly appreciated. Thanks and regards,