The Nyquist frequency is shockingly easy: Google just produced for
me about 766,000 hits. The first two I checked said the Nyquist
frequency is half the sampling rate (e.g.,
http://en.wikipedia.org/wiki/Nyquist_frequency). Therefore, with daily
numbers, the Nyquist frequency is 0.5 days, which means you can detect
patterns that occur on alternate days.
If it were my problem, I would spend my time trying to correlate any
cycles with known physical phenomena, like the annual weather patterns
and the phases of the moon. I hope some spectral wizard will enlighten
me, but the primary value I've gotten from things like spectral analysis
is to push me and others to think of other phenomena that occur at the
special identified frequencies.
This logic pushes me to ask why you think there might be oscillations
with periods of 10-20 days?
Beyond this, I suggest you consider the functions arima and
KalmanLike in the Stats package, the time series chapter in Venables and
Ripley (2002) Modern Applied Statistics with S, 4th ed. (Springer). If
you do not have reasonable access to this latter book, I encourage you
to tell your management that it comes most highly recommended, and that
the purchase of a copy will be an exceptionally good investment, in my
judgment.
Hope this helps.
spencer graves
anil kumar rohilla wrote:
>
> Hi List,
> I have a time series of 122 values, actualy it is
a time series of daily indian monsoon rainfall. now i want to
filter this time series for a particular oscilation say 10 to
20days oscilation. i want to find out what amount of variance
is explained by this mode. Which package is available in R for
this purpose. and how to calculate nquest frequancy of this
series. any help is much appriciated.
>
> thanks in advance
> anil
>
>
> ANIL KUMAR( METEOROLOGIST)
> LRF SECTION
> NATIONAL CLIMATE CENTER
> ADGM(RESEARCH)
> INDIA METEOROLOGICAL DEPARTMENT
> SHIVIJI NAGAR
> PUNE-411005 INDIA
> MOBILE +919422023277
> [EMAIL PROTECTED]
>
> [[alternative HTML version deleted]]
>
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