[R] X-12-ARIMA

[Alistair Gray]

Dear All,
I've used the X-12-ARIMA or its earlier versions from S+ and R under both Unix 
and Windows platforms for many years using the klugey approach of calling an 
executable using in R the system function.  I've found this serviceable  for the 
following reasons.

1) Paul Gilbert's hunch is correct that many of the subroutines have extensive 
IO calls (especially the X-11 engine) and so it is not straightfoward to call 
using .Fortran.

2) X-12-ARIMA has in the Unix final version 0.2.10 which I use 15 different 
commands with their own parameters covering about six pages of description so 
it's not clear to me having a long R function parameter list is a great advantage.

My experience with people who have ported X-12-ARIMA into other econometrics 
software is that they port a limited range of the commands and options. (I'd be 
interested to know from Dirk Eddelbuettel if this is the case for GNU-Gretl.)

3) X-12_ARIMA through its specification files (particularly the metafiles) is 
set up to handle multiple runs on different time series with different parameter 
settings. I'm not sure I'd want to re-invent it. Secondly I find it an OK way to 
keep track of what I've done.

However, I'd be a grateful user of a less klugey approach.

Below is a clearer explanation of my klugey approach and functions which I've 
used successfully. Feel free to use them.

# create data file for the series to be read by  x12 fortran pgm
# blp is a object of class ts written to file blp.dat in the x12 datevalue
# format

writex12in(blp,"blp")

# create the specification file using your favourite editor say blp.spc to be
# read by x12 fortran pgm
# a vanilla specification file might have the following

# series{
#   title="building consents"
#   start=1973.01
#   span=(1973.01, 2000.12)	
#   period=12
#   file="blp.dat"
#   format="datevalue"
# }

# x11{
#   mode=mult
#   sigmalim=(1.8 2.8)
#   seasonalma=x11default
#   trendma=13
#   appendfcst=no
#   save=(b1 c17 d10 d11 d12 d13)
#   savelog=(m1 m2 m3 m4 m5 m6 m7 m8 m9 m10 m11 q q2 msr icr fb1 fd8 msf ids)
# }


# execute the  x12 fortran pgm. executable x12a stored in /home/fred/x12a

system("/home/fred/x12a/x12a blp")


# read  x12 fortran pgm output tables back into R

blp.x12 <- readx12out("blp", adtype="M", calendar=F, tblnames=NULL)


# basic versions of writex12in  and readx12out

writex12in <- function(tso,file){
   write.table(cbind(time(tso) %/% 1, cycle(tso), tso),
               file=paste(file,".dat",sep=""),
               sep=" ", quote=F, row.names=F, col.names=F)
}


readx12out <- function(file, adtype = "M", calendar = F, tblnames = NULL) {
	notbls <- 6 + (calendar != F) + length(tblnames)
	comp <- vector("list", notbls)
	if(calendar == F) {
		names(comp) <- c("original", "seasonal", "adjusted", "trend",
                                  "irregular", "weights", tblnames)
		tblnames <- c("b1", "d10", "d11", "d12", "d13", "c17", tblnames)
	}
	else {
		names(comp) <- c("original", "seasonal", "adjusted", "trend",
                                  "irregular", "calendar", "weights", tblnames)
		if(calendar == "C")
			tblnames <- c("b1", "d10", "d11", "d12", "d13", "xca", "c17",
				tblnames)
		else tblnames <- c("b1", "d10", "d11", "d12", "d13", "c16", "c17",
				tblnames)
	}
	for(i in seq(along = comp)) {
		series <- read.table(paste(file, ".", tblnames[i], sep = ""),
			as.is = T, skip = 2)
                 times <- series[,1]
                 begin <- c(times[1]%/%100,times[1]%%100)
                 freq <- max(times%%100)
		comp[[i]] <- ts(data = series[,2], start = begin, frequency = freq)
	}
# for the log transform the adjusted series is the log of the original
# also x12 transforms trend, seasonal, etc back into original scale
# i.e. making a multiplicative decomposition in which case 1.0 needs to be
# subtracted from seasonal, irregular and calendar to be consistent with
# multiplicative. Also x12 makes correction for bias to trend in original scale
# so best to treat as multiplicative decomposition rather than decomposition in
# transformed scale
	if(adtype == "L") {
		comp$transformed <- comp$original
		comp$seasonal <- comp$seasonal - 1
		comp$irregular <- comp$irregular - 1
		if(calendar != F)
			comp$calendar <- comp$calendar - 1
		comp$power <- "log additive presented as multiplicative. 1.0 has been 
subtracted from seasonal, irregular & calendar (if present)"
	}
	else if(adtype == "M") {
		comp$transformed <- comp$original
		comp$seasonal <- comp$seasonal - 1
		comp$irregular <- comp$irregular - 1
		if(calendar != F)
			comp$calendar <- comp$calendar - 1
		comp$power <- "multiplicative. 1.0 has been subtracted from seasonal, 
irregular & calendar (if present)"
	}
	else if(adtype == "A") {
		comp$original <- rtso
		comp$power <- "additive"
	}
	return(comp)
}




-- 
Alistair Gray                       Email:  alistair at statsresearch.co.nz
Statistics Research Associates Ltd  Web:    www.statsresearch.co.nz
PO Box 12 649, Thorndon, Wellington Phone:  +64 +4 972 6531
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