[R] library(forecast): Error in SD.test(x, m) : Insufficient data

[Rainer Hurling]

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<rhurlin at gwdg.de>  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