[R] Problems with arima0 (almost solved)

[Pascal Grandeau]

I think I found what was wrong : if I do scaling on the matices y and xreg,
all seems good. Here is what I do :

> dd<-read.csv2("c:/modelfr2.csv")
> y<-dd[,1]
> x<-dd[,-1:-2]
> x1<-scale(x)
> y1<-scale(as.matrix(as.double(y)))
> ari<-arima0(y1,xreg=as.matrix(x1),order=c(1,0,3))

and I got :

> ari$coef
            ar1             ma1             ma2             ma3
intercept

0.981959774    -0.133513133    -0.313765424    -0.120906582    -0.014087163
       TempLT17            lag2              We        hivergaz
lag7
    0.595713158     0.081242497    -0.074302282     0.121198338
0.049151266
        octobre        vendredi       Tmoycarre           Tmaxi
avril
   -0.046997365    -0.024616056
 0.401650456    -0.067899417    -0.062226297
       TempGT17        vacances     Lineartrend       TempLT171
feriesemaine
   -0.174204375    -0.010849255    -1.593994601
 0.094049181    -0.015111721
         vacoct    MoistransT17           jeudi        mercredi
Tmoycarre1
    0.002894903     0.066673677    -0.008290431    -0.004808032
0.048113321
          WET17          vacdec    MoistransTnx       septembre
MoistransDeltaT
   -0.018610689    -0.021541452     0.028866118    -0.060574403
0.024856178
 MoistransDTmax   Rechauffement          samedi         janvier
automne
   -0.011687046     0.004914881    -0.007455964    -0.008352493
0.037430983
        periode     quadratrend            aout         tempeff
MoistransDTmin
   -0.812194507
 1.614215908    -0.004387879    -0.050769121    -0.005031441
  MoistransTmin           hiver            juin
    0.026752595     0.027127835     0.007552805


> sqrt(diag(ari$var.coef))
            ar1             ma1             ma2             ma3
intercept
    0.010172128     0.042899460     0.051893431     0.039494948
0.057324206
       TempLT17            lag2              We        hivergaz
lag7
    0.020040066     0.027233295     0.004830991     0.028450063
0.015719575
        octobre        vendredi       Tmoycarre           Tmaxi
avril
    0.023873606     0.003941548     0.033016873     0.013613845
0.019573895
       TempGT17        vacances     Lineartrend       TempLT171
feriesemaine
    0.016457262     0.008907412     0.401197993     0.020490511
0.002024213
         vacoct    MoistransT17           jeudi        mercredi
Tmoycarre1
    0.005764023     0.015146301     0.003811101     0.003136478
0.021529475
          WET17          vacdec    MoistransTnx       septembre
MoistransDeltaT
    0.004133053     0.007681165     0.021842469     0.023770587
0.005238365
 MoistransDTmax   Rechauffement          samedi         janvier
automne
    0.003566694     0.001953077     0.002418192     0.012942518
0.015704967
        periode     quadratrend            aout         tempeff
MoistransDTmin
    0.208897607     0.413539315     0.011196934     0.043177465
0.003314960
  MoistransTmin           hiver            juin
    0.026484594     0.016473332     0.008654350

The only problem now is : how can I retrieve now the true coefficients and
the true se for the non scaled regressors and intercept ?

Can anyone help me ?

Thank you very much.

Pascal Grandeau

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