Thanks for everyone's help with zoo -- I think I've got my data set
ready. (The data consists of surface weather temperatures, from 2002
to 2005, one observation per hour. Some values are missing... i.e. NA)
I have three goals:
GOAL #1:Get the data in proper time series form, preserving frequency
information:
> w4.ts <- as.ts( w3.zoo, frequency=(1/3600) )
I hope that 1/3600 (0.0002778) is correct. I chose it because my
zooreg object reported that value. This goes back to my choice of
the ISOdatetime format, which required deltat=3600.
GOAL #2: Do an ARIMA analysis that takes into account seasonal variation
> a.1 <- arima(w4.ts,order=c(1,0,0),seasonal=list(order=c
> (0,1,0),period=12))
First, I'm not quite sure if I should set period=12 (months in a
year) or period=365*24 (number of my observations in a year). The
documentation was unclear to me.
Second, I've noticed that the fracdiff command is useful to find
appropriate (p,d,q) values for ARIMA models. But I have not found a
command that suggests reasonable values for the seasonal (p,d,q) values.
GOAL #3 Use the ARIMA analysis to fill in for NA values. (I'm not
sure how to do this yet. For example, I do not know if I will need
to use windowing to smooth my backcasted data.
I would appreciate any pointers, references, or code examples.
Also, the terminology of "backcasting" and "interpolation" is not
perfectly clear to me. I'm certainly looking to do more than linear
interpolation between data points ... that's why I'm hoping that
ARIMA will help. I need seasonal ARIMA, I believe, because there are
seasonal swings in temperature
Thanks,
David
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