Hi Everybody,

My problem is that nlminb doesn't converge, in minimising a logLikelihood
function, with 31*6 parameters(2 weibull parameters+29 regressors repeated 6
times).


I use nlminb like this :
res1<-nlminb(vect, V, lower=c(rep(0.01, 12), rep(0.01, 3), rep(-Inf, n-15)),
upper=c(rep(Inf, 12), rep(0.99, 3), rep(Inf, n-15)), control =
list(maxit=1000) )

and that's the result :

Message d'avis :
In nlminb(vect, V, lower = c(rep(0.01, 12), rep(0.01, 3), rep(-Inf,  :
  unrecognized control element(s) named `maxit' ignored
> res1
$par
  [1]   2.48843979   4.75209125   2.57199837  16.80712783   3.15211075
16.86606178  58.61925499  37.85793462  48.78215699
 [10] 151.64638501  43.60420299  15.14639541   0.58754382   0.76180935
0.66191763  -0.26802757  -0.96378197  -0.68369525
 [19]   0.37813096   0.89778593 -10.26471908  -0.87265813   6.43973968
-1.74417166  12.00193419   0.60638326  -1.66675589
 [28]   1.29312079   1.39846863  -0.48449361  20.14470193  -0.50729841
-2.15177967  -0.78155345   0.41857810  -0.40863744
 [37] -17.18489562  -1.69140562   1.45236861  -0.23738183   5.47688642
-0.71546576   9.95015047  -2.16096138  -0.74503151
 [46]  -0.66258461   5.38871217   2.53147752 -12.58827379  -0.45669589
-0.37285088   2.15116198  -2.50414066  -0.99752892
 [55]   4.83972450  -1.16496925  -3.53429528   0.56083677  -9.87490932
-1.75153657   9.87912224  -0.75783517  -9.95423392
 [64]  -0.07530469  -0.73466191  -0.27397382  15.15891548  -0.02489436
12.91493065  -4.65335356   0.03524561   0.00000000
 [73]  -9.06720312  -0.25413758  -0.18578765   0.53283198  -4.02688497
-0.50581412  -0.31544940   0.57450848   6.15206152
 [82]   0.08178377   0.82978606   0.39337352  -3.65304712  -0.06833839
3.87790848  -1.08017043   3.62779184  -0.14700541
 [91] -13.95610827  -1.50385432   8.05851743  -1.24250013  -0.01249817
0.38085483  -4.97064573  -0.98852401  -3.00305183
[100]   0.35053875  -4.26833889  -0.12463188  16.05828402   0.41736764
-0.94678922  -0.75813452   2.15378348   0.39586048
[109]   1.41359441   0.81603207  -4.43963958  -0.79438435   0.49530882
0.11197484  -8.43196798   1.00456535 -22.04423030
[118]  -0.11532887   2.58085765   1.41912515  -0.78120889  -1.23850824
12.39079062   0.23567444   1.39557879  -2.22993802
[127] -12.58827379  -0.45669589  -0.37285088  -0.73563805   3.40201735
0.58550247  -3.62769828   0.21657740  -7.37785506
[136]  -0.68218180   6.41876225   0.38708385  -0.33009429  -0.25230736
3.53672719   1.53676202   3.65074513   0.42623602
[145]  -7.26982010   0.70597611 -23.15198788  -0.36822845  -2.29863267
0.70223129 -14.45665129  -0.54094864  -2.17858443
[154]  -0.56501734   2.50032796  -0.45677181  12.04113439  -1.42294094
-16.16874444  -0.49101846  -6.29724769  -1.38333722
[163] -14.16552579   1.57502968   5.04329383   0.24857745  -1.69885428
-0.46757266   4.41795651  -2.41006349   4.61648610
[172]   0.42235314  -3.22153895  -0.15443857   1.07661101  -0.63653449
-2.74034265   0.20898466   1.37927183   0.26722477
[181] -15.09685067   0.87160467 -24.79722150   1.48810684   1.70068893
-0.22538026   7.63908028   1.60431981  -7.52661064

$objective
[1] 1514.691

$convergence
[1] 1

$message
[1] "iteration limit reached without convergence (9)"

$iterations
[1] 150

$evaluations
function gradient
     176    44935

I tried many times to take the res1$par as initial values and retry againe
but still doesn't converge.


Any help will save me Thanks

-- 
Kamel Gaanoun
(+33) (0)6.76.04.65.77

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