One of the most important concepts is most certainly Stationarity (see ?unit
root test").
the most common r-package will be: tseries.
see:
Brockwell/Davis (2006): Time Series: Theory and Models.
Brockwell/Davis (2002): Introduction to Time Series and Forecasting.
Cowpertwait/Metcalfe (2009): Introductory Time Series with R.
Cryer/Chan (2008): Time Series Analysis: With Applications in R.
for some general introductions of using time series in r.
Am 01.06.2012 um 14:49 schrieb Pierre Antoine DuBoDeNa:
>>
>> Hello,
>>
>> I am trying to collect several global measures or statistics for
>> time-series as well as packages of R that can compute them. I have
found
>> several of them in papers and books, but the literature is so big i am
sure
>> i am missing several of them.
>>
>> skewness
>> kurtosis
>> min
>> max
>> mean
>> SD
>> trend
>> seasonality
>> periodicity
>> chaos (Lyapunov Exponent) / Largest Lyapunov Exponent (i think is the
same
>> statistic)
>> serial correlation / auto-correlation (this is the same if i am correct
>> Box-Pierce autocorrelation sum)
>> higher-order autocorrelation
>> nonlinearity (terasvirta test)
>> self similarity (Hurst exponent)
>> matual information sum
>>
>> any other statistics that i am missing? Maybe other useful tests?
>>
>> or books/papers that i could find more?
>>
>> also any packages that can compute some/all of them?
>>
>> Best,
>> PA
>>
>>
>>
>>
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at 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.