Actually to get exactly what I want I need to add
no.dimnames(AvgDemand )

where
no.dimnames <- function(a) {
       ## Remove all dimension names from an array for compact printing.
       d <- list()
       l <- 0
       for(i in dim(a)) {
         d[[l <- l + 1]] <- rep("", i)
       }
       dimnames(a) <- d
       a
     }



Thanks

Paolo



On 6 July 2011 11:06, Paolo Rossi <statmailingli...@googlemail.com> wrote:

> Hello,
>
> the more general thing I'd like to learn here is how to compute Function of
> Data on the basis of grouping determiend by n variables.
>
> In terms of the reason why I am interested in this, I need to compute the
> average of my data based on the value of the month and day across years. I
> have come up withy the code below which, as far as I can see, does what I
> need but getting either a more elegant or a more versatile way to do this
> would be nice.
>
> Thanks
>
> Paolo.
>
> Days = format(as.Date(Data[["GasDays"]], format = "%d/%m/%Y"), "%d")
> Months = format(as.Date(Data[["GasDays"]], format = "%d/%m/%Y"), "%m")
> MonthDayCombs = paste(Months, Days)
> AvgDemand = data.matrix(by(Data$RescaledDemand,  DayMonthCombs, mean))
>
>
>
> On 4 July 2011 10:34, EdBo <n.bow...@gmail.com> wrote:
>
>> Hi
>>
>> May you help me correct my loop function.
>>
>> I want optim to estimates al_j; au_j; sigma_j;  b_j by looking at 0 to 20,
>> 21 to 40, 41 to 60 data points.
>>
>> The final result should have 4 columns of each of the estimates AND 4 rows
>> of each of 0 to 20, 21 to 40, 41 to 60.
>>
>> ###MY code is
>>
>> n=20
>> runs=4
>> out=matrix(0,nrow=runs)
>>
>> llik = function(x)
>>   {
>>    al_j=x[1]; au_j=x[2]; sigma_j=x[3];  b_j=x[4]
>>    sum(na.rm=T,
>>        ifelse(a$R_j< 0, -log(1/(2*pi*(sigma_j^2)))-
>>                           (1/(2*(sigma_j^2))*(a$R_j+al_j-b_j*a$R_m))^2,
>>         ifelse(a$R_j>0 , -log(1/(2*pi*(sigma_j^2)))-
>>                           (1/(2*(sigma_j^2))*(a$R_j+au_j-b_j*a$R_m))^2,
>>
>> -log(pnorm(au_j,mean=b_j*a$R_m,sd=sqrt(sigma_j^2))-
>>                           pnorm(au_j,mean=b_j*a$R_m,sd=sqrt(sigma_j^2)))))
>>
>>       )
>>
>>   }
>>
>> start.par = c(0, 0, 0.01, 1)
>> out1 = optim(llik, par=start.par, method="Nelder-Mead")
>>
>>
>> for (i in 1: runs)
>> {
>>  index_start=20*(i-1)+1
>>  index_end= 20*i
>>  out[i]=out1[index_start:index_end]
>> }
>> out
>>
>>
>> Thank you in advance
>>
>> Edward
>> UCT
>> ####My data
>>
>> R_j             R_m
>> -0.0625         0.002320654
>> 0               -0.004642807
>> 0.033333333     0.005936332
>> 0.032258065     0.001060848
>> 0               0.007114057
>> 0.015625        0.005581558
>> 0               0.002974794
>> 0.015384615     0.004215271
>> 0.060606061     0.005073116
>> 0.028571429     -0.006001279
>> 0               -0.002789594
>> 0.013888889     0.00770633
>> 0               0.000371663
>> 0.02739726      -0.004224228
>> -0.04           0.008362539
>> 0               -0.010951605
>> 0               0.004682924
>> 0.013888889     0.011839993
>> -0.01369863     0.004210383
>> -0.027777778    -0.04658949
>> 0               0.00987272
>> -0.057142857    -0.062203157
>> -0.03030303     -0.119177639
>> 0.09375         0.077054642
>> 0               -0.022763619
>> -0.057142857    0.050408775
>> 0               0.024706076
>> -0.03030303     0.004043701
>> 0.0625          0.004951088
>> 0               -0.005968731
>> 0               -0.038292548
>> 0               0.013381097
>> 0.014705882     0.006424728
>> -0.014492754    -0.020115626
>> 0               -0.004837891
>> -0.029411765    -0.022054654
>> 0.03030303      0.008936428
>> 0.044117647     8.16925E-05
>> 0               -0.004827246
>> -0.042253521    0.004653096
>> -0.014705882    -0.004222151
>> 0.029850746     0.000107267
>> -0.028985507    -0.001783206
>> 0.029850746     -0.006372981
>> 0.014492754     0.005492374
>> -0.028571429    -0.009005846
>> 0               0.001031683
>> 0.044117647     0.002800551
>>
>>
>>
>>
>>
>>
>>
>>
>>
>>
>>
>>
>> --
>> View this message in context:
>> http://r.789695.n4.nabble.com/loop-in-optim-tp3643230p3643230.html
>> Sent from the R help mailing list archive at Nabble.com.
>>
>> ______________________________________________
>> R-help@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
>

        [[alternative HTML version deleted]]

______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Reply via email to