[R] Maximum likelihood estimate of bivariate vonmises-weibulldistribution

Chaouch, Aziz achaouch at NRCan.gc.ca
Fri May 12 15:13:20 CEST 2006

Thanks a lot! I wasn't aware of that copula package and it could well be
appropriate to use it for my application. However if I read the copula
help correctly, I still need to know what kind of copula to use to link
the distribution of wind speeds and directions. Is there a way to
determine this in R?

Moreover can I use the Von Mises distribution from the circular or
CircStats package into the mvdc function of the copula package or does
the mvdc function only recognize distributions available "natively"
within R?

Thanks again to all, your help is highly appreciated for a newbie like



-----Original Message-----
From: Dimitris Rizopoulos [mailto:dimitris.rizopoulos at med.kuleuven.be] 
Sent: May 12, 2006 3:01 AM
To: Philip He; Chaouch, Aziz
Cc: r-help at stat.math.ethz.ch
Subject: Re: [R] Maximum likelihood estimate of bivariate

----- Original Message -----
From: "Philip He" <hydinghua at gmail.com>
To: "Chaouch, Aziz" <achaouch at nrcan.gc.ca>
Cc: <r-help at stat.math.ethz.ch>
Sent: Thursday, May 11, 2006 11:21 PM
Subject: Re: [R] Maximum likelihood estimate of bivariate

> On 5/11/06, Chaouch, Aziz <achaouch at nrcan.gc.ca> wrote:
>> 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.
> In order to built a bivariate distribution from two marginal 
> distributions (wind direction, wind speed) , more information is 
> needed to specify the relation between these two marginal 
> distributions.For example, a conditional distribution may help.

An alternative in such cases (i.e., when marginals are available but the
joint is difficult to postulate) is to use copulas, which can construct
multivariate distributions from univariate marginals. If this is
appropriate for this application, the "copula" package might be of help.


Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven

Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/(0)16/336899
Fax: +32/(0)16/337015
Web: http://www.med.kuleuven.be/biostat/

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