R help - Aug 2010 - Dealing with a lot of parameters in a function

Hi all,
     I'm trying to define and log-likelihood function to work with MLE.
There will be parameters like mu_i, sigma_i, tau_i, ro_i, for i between
1 to 24. Instead of listing all the parameters, one by one in the
function definition, is there a neat way to do it in R ?  The example is
as follows:

 ll<- function(mu1=-0.5,b=1.2,tau_1=0.5,sigma_1=0.5,ro_1=0.7)
{ if (tau1>0 && ro<1 && ro>-1) 
 
-sum(dmnorm(cbind(x,y),c(mu1,b*mu1),matrix(c(tau_1^2,ro_1*tau_1*sigma_1,
ro_1*tau_1*sigma_1,sigma_1^2),nrow=2),log=T))
   else NA
}

but now I need to have the sum of 24 of these negative log-likelihood.

Thanks.

Yue
Notice:  This e-mail message, together with any attachme...{{dropped:11}}

use 24 length vectors as parameters instead of numbers e.g. mu=rep(0.5,24)

On Mon, Aug 2, 2010 at 11:00 AM, Shentu, Yue <yue_shentu@merck.com> wrote:
> Hi all,
>     I'm trying to define and log-likelihood function to work with MLE.
> There will be parameters like mu_i, sigma_i, tau_i, ro_i, for i between
> 1 to 24. Instead of listing all the parameters, one by one in the
> function definition, is there a neat way to do it in R ?  The example is
> as follows:
>
>  ll<- function(mu1=-0.5,b=1.2,tau_1=0.5,sigma_1=0.5,ro_1=0.7)
> { if (tau1>0 && ro<1 && ro>-1)
>
> -sum(dmnorm(cbind(x,y),c(mu1,b*mu1),matrix(c(tau_1^2,ro_1*tau_1*sigma_1,
> ro_1*tau_1*sigma_1,sigma_1^2),nrow=2),log=T))
>   else NA
> }
>
> but now I need to have the sum of 24 of these negative log-likelihood.
>
> Thanks.
>
> Yue
> Notice:  This e-mail message, together with any attachme...{{dropped:11}}
>
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>
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Hi,

Putting all parameters into a data frame would help.

Code like:

parameters <-
data.frame(mu=1:24,b=(1:24)*2,tau=(1:24)/2,sigma=(1:24)^2,ro=sqrt(1:24))

ll<- function(parameters){
	results <- numeric(24)
	for (i in 1:24){
	mu <- parameters$mu[i]
	b <- parameters$b[i]
	.....
	results[i] <- sum(mu*b)
	}
	results
}
sum(results)

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