similar to: generate bivariate or multivariate gamma distribution in R

Hi, there. Does anyone know the R function for calculating the cdf of bivariate normal distribution function? Thanks. Yulei [[alternative HTML version deleted]]

Hello. I have yet to receive a response to my previous post, so I may have done a poor job asking the question. So, here is the general question: how can I run a run a multivariate (more than one non-independent, response variables) ordered probit regression model? I've had success doing this in the univariate case using the vglm() function in the VGAM package. For example:

Greetings, I'm interested in generating data from various bivariate or mulitivariate distributions (e.g. gamma, t, etc), where I can specify the parameter values, including the correlations among the variables. I haven't been able to dig anything up on the faq, but I probably missed something. A nudge in the right direction would be appreciated. David --

Hi, there. I have two questions about the diagnostics in multivarite statistics. 1. Is there any diagnostics tool to check if a multivariate sample is from multivariate normal distribution? If there is one, is there any function doing it in R? 2. Is there any function of testing if two multivariate distribution are same, i.e. the multivariate extension of Kolomogrov-Smirnov test? Thanks for

Hi,Dear all R experts, As far as I know, fitdistr() is only to estimate the parameters in univariate distributions. I have a set of data (x,y) and I assume it follows a bivariate weibull distribution. Could someone tell me a function in R that is suitable for parameter estimation in multivariate cases? Thanks in advance! Cheers, YAN

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

Dear All I want to generate variable with Bivariate Normal Distribution by use mean1 = a, variance1 = b, mean2 = c, variance2 = d, rho = e. How I can do this. Many Thanks. IRD [[alternative HTML version deleted]]

Hi, there. Suppose I have a bivarariate data matrix y1 and y2. I want to plot a 3-D picture of the estimated density f(y1, y2) against y1 and y2? How can I do that? Do I use persp() or density()? Thanks for your help. Yulei $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$ Yulei He 1586 Murfin Ave. Apt 37 Ann Arbor, MI 48105-3135 yuleih at umich.edu 734-647-0305(H) 734-763-0421(O) 734-763-0427(O)

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]]

Hi, How can I generate data from multivariate gamma distribution & multivariate beta distribution? I only found command for multivariate normal only. Many thanks in advance :) Regards Rofizah [[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:

Could somebody share some tips on implementing multivariate integration and partial differentiation in R? For example, for a trivariate joint distribution (cumulative density function) of F(x,y,z), how to differentiate with respect to x and get the bivariate distribution (probability density function) of f(y,z). Or integrate f(x,y,z) with respect to x to get bivariate distribution of (y,z). Your

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

Hello R-Team, I am trying to construct a Copula from a multivariate Gamma distribution with its marginals gamma-distributed. The multivariate Gamma should be able to contain a correlation coeficient or matrix. I have studied the book "Continuous Multivariate Distributions vol.I Models and applications" by Johnson & Kotz & Balakrishnan but what I constructed doesn't really

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

Dear Community, For my masters thesis I need to perform a multivariate granger causality test. I have found a code for bivariate testing on this page (http://www.econ.uiuc.edu/~econ472/granger.R.txt), which I think would not be useful for the multivariate case. Does anybody know a code for a multivariate granger causality test. Thank you in advance. Best Regards -- View this message in context:

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

Hello, I am searching for a way to generate random values from a multivariate mixture distribution. For starters, one could create a mixture distribution consisting of a gamma or normal distribution and then a tail/spike of values in a normal distribution (eg as in Figure 1,?A Eyre-Walker, PD Keightley. 2007. The distribution of fitness effects of new mutations. Nature Review Genetics 8: 610-618)

"Jenny Stadt" <jennystadt at yahoo.ca> asked: > > I am struggling in a bivariate Weibull distribution although I > searched R-Site-Help and found suggestion with Copula. Seems the > maximum likelihood estimate is beyond what I can understand. > > My case is: given two known marginal distribution (both are Weibull), > and the correlation between them. How can I

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