[R] ARIMA (seasonal) backcasting & interpolation

From: David James <djames_at_frontierassoc.com>
Date: Sat 27 Aug 2005 - 11:41:49 EST

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


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