R help - May 2013 - maxLik: different estimations from different packages

Dear all,

we are computing maximum likelihood estimations using maxLik package  
and we realized that the results of the estimation depend on the  
version of the package installed

for example if we try to estimate this function with an old version of  
maxLik under R 2.13.1 (32 bit version installed 2 years ago):


L<-function (param) {b0t<-param[1]
                      p1t<-param[2]
                      p2t<-param[3]
                      p3t<-param[4]
                      p4t<-param[5]

for(i in 17:T) {n[i,]<- b0t + p1t*a[i-1] + p2t*sum(a[(i-4):(i-1)]) +  
p3t*(sum(a[(i-8):(i-1)])) + p4t*(sum(a[(i-16):(i-1)]))
                m[i,]<-exp(n[i])/(1+exp(n[i]))
                ll[i-16,]<-a[i]*log(m[i])+(1-a[i])*log(1-m[i]) }
                      sum(ll)}
b2<-maxLik(L, start=c(-2.8158,5,-1,0.3213,-0.3112))


we obtain this results:

summary(b2)

Maximum Likelihood estimation
Newton-Raphson maximisation, 16 iterations
Return code 2: successive function values within tolerance limit
Log-Likelihood: -38.11285
5  free parameters
Estimates:
       Estimate Std. error t value   Pr(> t)
[1,]  -2.81578    0.43548 -6.4660 1.007e-10 ***
[2,]  50.50024   13.17046  3.8344 0.0001259 ***
[3,] -11.53344    3.31075 -3.4836 0.0004947 ***
[4,]   0.32130    0.42978  0.7476 0.4547096
[5,]  -0.31121    0.23245 -1.3388 0.1806280
---
Signif. codes:  0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
--------------------------------------------

NB: a is a binary time series

if we try to estimate the same function using the last version of  
maxLik under R.3.0 (64 bit latest version) the estimation do not  
converge and this is the error message:

Iteration 15
Parameter:
[1]  -2.8146429  51.3042554 -11.7373313   0.3245214  -0.3125767
Gradient:
[1] NaN NaN NaN NaN NaN
Errore in maxNRCompute(fn = logLikAttr, fnOrig = fn, gradOrig = grad, 
hessOrig = hess,  :
   NA in gradient

What causes this?

Thanks
Alfonso





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Dear Alfonso

On 10 May 2013 12:51,  <alfonso.carfora at uniparthenope.it>
wrote:
> we are computing maximum likelihood estimations using maxLik package and we
> realized that the results of the estimation depend on the version of the
> package installed
>
> for example if we try to estimate this function with an old version of
> maxLik under R 2.13.1 (32 bit version installed 2 years ago):
>
>
> L<-function (param) {b0t<-param[1]
>                      p1t<-param[2]
>                      p2t<-param[3]
>                      p3t<-param[4]
>                      p4t<-param[5]
>
> for(i in 17:T) {n[i,]<- b0t + p1t*a[i-1] + p2t*sum(a[(i-4):(i-1)]) +
> p3t*(sum(a[(i-8):(i-1)])) + p4t*(sum(a[(i-16):(i-1)]))
>                m[i,]<-exp(n[i])/(1+exp(n[i]))
>                ll[i-16,]<-a[i]*log(m[i])+(1-a[i])*log(1-m[i]) }
>                      sum(ll)}
> b2<-maxLik(L, start=c(-2.8158,5,-1,0.3213,-0.3112))
>
>
> we obtain this results:
>
> summary(b2)
>
> Maximum Likelihood estimation
> Newton-Raphson maximisation, 16 iterations
> Return code 2: successive function values within tolerance limit
> Log-Likelihood: -38.11285
> 5  free parameters
> Estimates:
>       Estimate Std. error t value   Pr(> t)
> [1,]  -2.81578    0.43548 -6.4660 1.007e-10 ***
> [2,]  50.50024   13.17046  3.8344 0.0001259 ***
> [3,] -11.53344    3.31075 -3.4836 0.0004947 ***
> [4,]   0.32130    0.42978  0.7476 0.4547096
> [5,]  -0.31121    0.23245 -1.3388 0.1806280
> ---
> Signif. codes:  0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
> --------------------------------------------
>
> NB: a is a binary time series
>
> if we try to estimate the same function using the last version of maxLik
> under R.3.0 (64 bit latest version) the estimation do not converge and this
> is the error message:
>
> Iteration 15
> Parameter:
> [1]  -2.8146429  51.3042554 -11.7373313   0.3245214  -0.3125767
> Gradient:
> [1] NaN NaN NaN NaN NaN
> Errore in maxNRCompute(fn = logLikAttr, fnOrig = fn, gradOrig = grad,
> hessOrig = hess,  :
>   NA in gradient
>
> What causes this?
It could be that the NaNs in the gradients are caused by rounding
errors and/or approximation errors in the numerical
(finite-difference) derivatives when using R.3.0 64 bit, because
different hardware and different software versions (e.g. R,
mathematical libraries, OS) could lead to different rounding errors.
In this case, the specification of a function that returns analytical
gradients could solve the problem.

If this does not solve the problem and you cannot find out the reason
for the NaNs in the analytical gradients yourself, please provide a
reproducible example so that we could help you with this.

Please note that you could also ask questions regarding the maxLik
package via a forum at maxLik's R-Forge site:

https://r-forge.r-project.org/projects/maxlik/


... and please do not forget to cite maxLik in your publications :-)

Best regards,
Arne


--
Arne Henningsen
http://www.arne-henningsen.name