Dear Gabor, Arne, Ravi, R users,
I am firstly trying the maximum likelihood approach, then will try the
Bayesian approach.
The likelihood function, and the log likelihood function, will depend on
the pdf of the error e in the formula:
y=f(theta*x)+e
Now let's say that e is Gaussian distri
For specific questions on the betareg package contact the maintainer.
If the likelihood based approaches are giving too much difficulty try
moving to a Bayesian framework (WinBUGS/R2WinBUGS, JAGS/r2jags, etc.)
On Wed, Mar 17, 2010 at 10:03 AM, Corrado wrote:
> Dear Arne, Gabor,
>
> I solved the p
Dear Arne, Gabor,
I solved the problem with betareg (downloaded the package). I run it on
my data, and unfortunately the constraint is definitively active, if I
remove the active variables, I then remove the most significant variables!
Of course the error is important, not the distribution o
On 17 March 2010 14:22, Gabor Grothendieck wrote:
> Contact the maintainer regarding problems with the package. Not sure
> if this is acceptable but if you get it to run you could consider just
> dropping the variables from your model that correspond to active
> constraints.
>
> Also try the maxL
Contact the maintainer regarding problems with the package. Not sure
if this is acceptable but if you get it to run you could consider just
dropping the variables from your model that correspond to active
constraints.
Also try the maxLik package. You will have to define the likelihood
yourself b
Dear Gabor,
1) The constraints are active, at least from a formal point view.
3) I have tried several times to run betareg.fit on the data, and the
only thing I can obtain is the very strange error:
Error in dimnames(x) <- dn : length of 'dimnames' [2] not equal to
array extent
The error i
Try it anyways -- maybe none of your constraints are active.
On Wed, Mar 17, 2010 at 6:01 AM, Corrado wrote:
> Dear Gabor, dear R users,
>
> I had already read the betareg documentation. As far as I can understand
> from the help, it does not allow for constrained regression.
>
> Regards
>
>
> Ga
Dear Gabor, dear R users,
I had already read the betareg documentation. As far as I can understand
from the help, it does not allow for constrained regression.
Regards
Gabor Grothendieck wrote:
Check out the betareg package.
On Tue, Mar 16, 2010 at 2:58 PM, Corrado wrote:
Dear R users
Check out the betareg package.
On Tue, Mar 16, 2010 at 2:58 PM, Corrado wrote:
> Dear R users,
>
> I have to fit the non linear regression:
>
> y~1-exp(-(k0+k1*p1+k2*p2+ +kn*pn))
>
> where ki>=0 for each i in [1 n] and pi are on R+.
>
> I am using, at the moment, nls, but I would rather
-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Corrado
Sent: Tuesday, March 16, 2010 2:59 PM
To: r-help@r-project.org
Subject: [R] Constrained non linear regression using ML
Dear R users,
I have to fit the non linear regression:
y~1-exp(-(k0+k1*p1+k2
Dear R users,
I have to fit the non linear regression:
y~1-exp(-(k0+k1*p1+k2*p2+ +kn*pn))
where ki>=0 for each i in [1 n] and pi are on R+.
I am using, at the moment, nls, but I would rather use a Maximum
Likelhood based algorithm. The error is not necessarily normally
distributed.
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