On 08.02.2012 17:19 (UTC+1), Jean Jacques Dureau wrote:
> Hi rainer,
> how can I control dependend packages?
You did not tell us very much about your installation and versions of
packages you are using.
On my system sessionInfo() gives me the following after loading your
example:
sessionInfo()
R Under development (unstable) (2012-02-07 r58290)
Platform: amd64-portbld-freebsd10.0 (64-bit)
locale:
[1]
de_DE.ISO8859-15/de_DE.ISO8859-15/de_DE.ISO8859-15/C/de_DE.ISO8859-15/de_DE.ISO8859-15
attached base packages:
[1] parallel stats graphics grDevices utils datasets methods
base
other attached packages:
[1] forecast_3.17 RcppArmadillo_0.2.34 Rcpp_0.9.9 fracdiff_1.4-0
[5] tseries_0.10-27 zoo_1.7-6 quadprog_1.5-4
loaded via a namespace (and not attached):
[1] grid_2.15.0 lattice_0.20-0
Here you can see, that package forecast uses other packages like
RcppArmadillo, Rcpp, fracdiff and others. If your dataset
'time.test.data' is ok, there is a (little) chance, that there are some
not updated packages used by forecast.
But I am for sure not an expert on this. Perhaps someone else has an idea?
Rainer
>
> thanks
>
> jj
>
> Il 08 febbraio 2012 17:10, Rainer Hurling<
[hidden email]> ha scritto:
>> On 08.02.2012 15:35 (UTC+1), Jean Jacques Dureau wrote:
>>>
>>> I have these R code:
>>>
>>>
>>> ###########################################################################
>>> time.test.data<-c(2.88645418326693, 2.91546949823027, 2.94130799329234,
>>> 2.93313338038109, 2.89478957915832, 2.86029757243540, 2.78648486664669,
>>> 2.80183167535133, 2.75435512226307, 2.78992352676563, 2.76028433151845,
>>> 2.68741721854305, 2.70691974293828, 2.683833847881, 2.65041551246537,
>>> 2.65169020111254, 2.58837541686517, 2.66549241844080, 2.58451314648945,
>>> 2.60250871080139, 2.61253722876188, 2.59921041087878, 2.71727961060032,
>>> 2.65440192667915, 2.74799149338374, 2.70649994101687, 2.80636027009366,
>>> 2.81801086502298, 2.82555635319454, 2.87133347201997, 2.75746714456392,
>>> 2.7660659236424, 2.71688375522241, 2.72655367231638, 2.72461997828447,
>>> 2.78455790784558, 2.71160702495708, 2.65754456439869, 2.85673280918507,
>>> 2.7053919591233, 2.7532637075718, 2.74272237196766, 2.75893306492199,
>>> 2.62584686181772, 2.75230602278893, 2.82781018027572, 2.80220656652931,
>>> 2.80242587601078, 2.84061953534849, 2.87123514783089, 2.76991605276683,
>>> 2.77796934865900)
>>>
>>> library(forecast)
>>> auto.arima(ts(time.test.data, start=c(2011,1), frequency=52))
>>>
>>> ###########################################################################
>>
>>
>> This looks good to me, I got no error:
>>
>> auto.arima(ts(time.test.data, start=c(2011,1), frequency=52))
>> Series: ts(time.test.data, start = c(2011, 1), frequency = 52)
>> ARIMA(2,0,2) with non-zero mean
>>
>> Coefficients:
>> ar1 ar2 ma1 ma2 intercept
>> 1.4540 -0.5762 -1.0235 0.5484 2.7569
>> s.e. 0.3351 0.3194 0.3240 0.1902 0.0328
>>
>> sigma^2 estimated as 0.003059: log likelihood=76.05
>> AIC=-140.09 AICc=-138.23 BIC=-128.38
>>
>>
>> So perhaps something is wrong with your data object or with your dependend
>> packages?
>>
>>
>>> I obtain the error message:
>>> Error in SD.test(x, m) : Insufficient data
>>>
>>> What is wrong?
>>>
>>> jj
______________________________________________
[hidden email] mailing list
https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide
http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
Locked
