R help - Nov 2011 - "Non-finite finite-difference value" error in eha's aftreg

Hi list!


I'm getting an error message when trying to fit an accelerated failure
time parametric model using the aftreg() function from package
eha:
> Error in optim(beta, Fmin, method = "BFGS", control = list(trace
>   as.integer(printlevel)),  :
> non-finite finite-difference value [2]
This only happens when adding four specific covariates at the same time
in the model (see below). I understand that kind of problem can come
from a too high correlations between my covariates, but is there
anything I can do to avoid it? Does something need to be improved in
aftreg.fit?

My data set is constituted of 34,505 observations (years) of 2,717
individuals, which seems reasonable to me to fit a complex model like
that (covariates are all factors with less than 10 levels). I can send
it by private mail if somebody wants to help debugging this.

The details of the model and errors follow, but feel free to ask for
more testing. I'm using R 2.13.1 (x86_64-redhat-linux-gnu), eha 2.0-5
and survival 2.36-9.


Thanks for your help!

> m <-aftreg(Surv(start, end, event) ~ homo1 + sexego + dipref1
+                                    + t.since.school.q,
+            data=ms, dist="loglogistic", id=ident)
Error in optim(beta, Fmin, method = "BFGS", control = list(trace
as.integer(printlevel)),  :
  non-finite finite-difference value [2]
Calls: aftreg -> aftreg.fit -> aftp0 -> optim
> traceback()
4: optim(beta, Fmin, method = "BFGS", control = list(trace
as.integer(printlevel)),
       hessian = TRUE)
3: aftp0(printlevel, ns, nn, id, strata, Y, X, offset, dis, means)
2: aftreg.fit(X, Y, dist, strats, offset, init, shape, id, control, 
       center)
1: aftreg(Surv(start, end, event) ~ homo1 + sexego + dipref1 + 
       t.since.school.q, data = ms, dist = "loglogistic", id = ident)

On Wed, Nov 16, 2011 at 3:06 PM, Milan Bouchet-Valat
<nalimilan@club.fr>wrote:
> Hi list!
>
>
> I'm getting an error message when trying to fit an accelerated failure
> time parametric model using the aftreg() function from package eha:
> > Error in optim(beta, Fmin, method = "BFGS", control =
list(trace > >   as.integer(printlevel)),  :
> > non-finite finite-difference value [2]
>
> This only happens when adding four specific covariates at the same time
> in the model (see below). I understand that kind of problem can come
> from a too high correlations between my covariates, but is there
> anything I can do to avoid it?

Yes, remove one (or more) covariate(s). The design matrix is almost
certainly singular.

Does something need to be improved in aftreg.fit?
>
Yes, error messages. I'll look at it.

Göran
>
> My data set is constituted of 34,505 observations (years) of 2,717
> individuals, which seems reasonable to me to fit a complex model like
> that (covariates are all factors with less than 10 levels).
>
I can send
> it by private mail if somebody wants to help debugging this.
>
> The details of the model and errors follow, but feel free to ask for
> more testing. I'm using R 2.13.1 (x86_64-redhat-linux-gnu), eha 2.0-5
> and survival 2.36-9.
>
>
> Thanks for your help!
>
>
> > m <-aftreg(Surv(start, end, event) ~ homo1 + sexego + dipref1
> +                                    + t.since.school.q,
> +            data=ms, dist="loglogistic", id=ident)
> Error in optim(beta, Fmin, method = "BFGS", control = list(trace
> as.integer(printlevel)),  :
>  non-finite finite-difference value [2]
> Calls: aftreg -> aftreg.fit -> aftp0 -> optim
>
> > traceback()
> 4: optim(beta, Fmin, method = "BFGS", control = list(trace >
as.integer(printlevel)),
>       hessian = TRUE)
> 3: aftp0(printlevel, ns, nn, id, strata, Y, X, offset, dis, means)
> 2: aftreg.fit(X, Y, dist, strats, offset, init, shape, id, control,
>       center)
> 1: aftreg(Surv(start, end, event) ~ homo1 + sexego + dipref1 +
>       t.since.school.q, data = ms, dist = "loglogistic", id =
ident)
>
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>


-- 
Göran Broström

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