similar to: simulate bivariate life time distributions

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

"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

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

Thanks Dimitris!!! That's much clearer now. Still have a lot of work to do this weekend to understand every bit but your code will prove very useful. Cheers, Aziz -----Original Message----- From: Dimitrios Rizopoulos [mailto:Dimitris.Rizopoulos at med.kuleuven.be] Sent: May 12, 2006 4:35 PM To: Chaouch, Aziz Subject: RE: [R] Maximum likelihood estimate of bivariate

You'll find that it is a lot easier to do it in R: # lets first simulate a bivariate normal sample library(MASS) bivn <- mvrnorm(1000, mu = c(0, 0), Sigma = matrix(c(1, .5, .5, 1), 2)) # now we do a kernel density estimate bivn.kde <- kde2d(bivn[,1], bivn[,2], n = 50) # now plot your results contour(bivn.kde) image(bivn.kde) persp(bivn.kde, phi = 45, theta = 30) # fancy contour with

Dear all, Is there any generic algorithm code for optimization implemented in R? I searched without success. Thanks, -- Zhu Wang Statistical Science Department Southern Methodist University Phone: (214)768-2453 Fax: (214)768-4035 Email: zhuw at mail.smu.edu

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

Dear useRs, upon request, the VGAM package (currently version 0.7-1) has been officially released on CRAN (the package has been at my website http://www.stat.auckland.ac.nz/~yee/VGAM for a number of years now). VGAM implements a general framework for several classes of regression models using iteratively reweighted least squares (IRLS). The key ideas are Fisher scoring, generalized linear and

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

R-Help I am attempting to create a series of bivariate normal distributions. So using the mvtnorm library I have created the following code ... # Standard deviations and correlation sig_x <- 1 sig_y <- 1 rho_xy <- 0.0 # Covariance between X and Y sig_xy <- rho_xy * sig_x *sig_y # Covariance matrix Sigma_xy <- matrix(c(sig_x ^ 2, sig_xy, sig_xy, sig_y ^ 2), nrow = 2, ncol = 2)

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 helpers, I am trying to use the mda package downloaded from the R website, but the data set has missing values so I got an error message. Should I manually handle these missing values? I was trying to read the documents to specify any option related to missing values, but I did not find it. Please forgive me if I ignore something obvious. Thanks, Zhu Wang Statistical Science Department

Dear R-users! I would like to fit exponential, Weibull and log-logistic via glm() like functions. Does anyone know a way to do this? Bellow is a bit longer description of my problem. Hm, could family() be adjusted/improved/added to allow for these distributions? SAS procedure GENMOD alows to specify deviance and variance functions to help in such cases. I have not tried that option and I do not

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, 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

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

Dear experts! Is there a package that enables to create the bivariate log-normal variables? Thanks a lot, Vicky Landsman. [[alternative HTML version deleted]]

Hi, I wish to simulate some data from a Weibull distribution. The rweibull function in R uses the parameterisation 'with shape parameter a and scale parameter b has density given by f(x) = (a/b) (x/b)^(a-1) exp(- (x/b)^a)'. However, it would be much more useful for me to simulate data using a different parameterisation of the Weibull, with shape a1 and scale b1, namely f(x) =

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:

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 --