~~ Methods for Function x12 in Package x12 ~~

~~ Methods for function x12 in package x12 ~~

x12(object,x12Parameter=new("x12Parameter"),x12BaseInfo=new("x12BaseInfo"),...)

Methods

signature(object = "ts")
signature(object = "x12Single")
signature(object = "x12Batch")

Arguments

object: object of class ts, x12Single-class or x12Batch-class
x12Parameter: object of class x12Parameter
x12BaseInfo: object of class x12BaseInfo
...: at the moment only forceRun=FALSE

Value

x12Output: An S4 object of class x12Output-class if object is of class ts
x12Single: An S4 object of class x12Single-class if object is of class x12Single-class
x12Batch: An S4 object of class x12Batch-class if object is of class x12Batch-class

Source

https://www.census.gov/data/software/x13as.html

Note

Parallelization is implemented for x12Batch objects with help of the package 'parallel'. To process in parallel set the option 'x12.parallel' to an integer value representing the number of cores to use ( options(x12.parallel=2) ). Afterwards all calls to the function 'x12' on an object of class 'x12Batch' will be parallelized (For reseting use options(x12.parallel=NULL) ).

cleanHistory is deprecated and cleanArchive should be used instead.

Author

Alexander Kowarik, Angelika Meraner

References

Alexander Kowarik, Angelika Meraner, Matthias Templ, Daniel Schopfhauser (2014). Seasonal Adjustment with the R Packages x12 and x12GUI. Journal of Statistical Software, 62(2), 1-21. URL http://www.jstatsoft.org/v62/i02/.

Examples

if (FALSE) {
xts <- x12(AirPassengers)
summary(xts)
xs <- x12(new("x12Single",ts=AirPassengers))
summary(xs)


xb<-x12(new("x12Batch",list(AirPassengers,AirPassengers,AirPassengers)))
summary(xb)

#Create new batch object with 4 time series
xb <- new("x12Batch",list(AirPassengers,AirPassengers,AirPassengers,AirPassengers))

# change the automdl to FALSE in all 4 elements
xb <- setP(xb,list(automdl=FALSE))
#change the arima.model and arima.smodel setting for the first ts object
xb <- setP(xb,list(arima.model=c(1,1,0),arima.smodel=c(1,1,0)),1)
#change the arima.model and arima.smodel setting for the second ts object
xb <- setP(xb,list(arima.model=c(0,1,1),arima.smodel=c(0,1,1)),2)
#change the arima.model and arima.smodel setting for the third ts object
xb <- setP(xb,list(arima.model=c(0,1,1),arima.smodel=c(1,1,1)),3)
#change the arima.model and arima.smodel setting for the fourth ts object
xb <- setP(xb,list(arima.model=c(1,1,1),arima.smodel=c(1,1,1)),4)
#run x12 on all series
xb <- x12(xb)
summary(xb)

#Set automdl=TRUE for the first ts
xb <- setP(xb,list(automdl=TRUE),1)

#rerun x12 on all series (the binaries will only run on the first one)
xb <- x12(xb)

#summary with oldOutput
summary(xb,oldOutput=10)

#Change the parameter and output of the first series back to the first run
xb <- prev(xb,index=1,n=1)

#summary with oldOutput (--- No valid previous runs. ---)
summary(xb,oldOutput=10)
}

Methods for Function `x12` in Package x12