demo/seas.R

require(seasonal)


# 'seas' ist the core function of the seasonal package. By default, 'seas'
# calls the automatic procedures of X-13ARIMA-SEATS to perform a seasonal
# adjustment that works well in most circumstances:

m <- seas(AirPassengers)

# The first argument of 'seas' has to be a time series of class "ts". It 
# returns an object of class "seas" that contains all necessary information 
# on the adjustment.

# The 'final' function returns the adjusted series:

final(m)

# The 'plot' method shows a plot with the unadjusted and the adjusted series: 

plot(m)

# The 'summary' method allows you to display an overview of the model:

summary(m)

# By default, 'seas' calls the SEATS adjustment procedure. If you prefer the X11
# adjustment procedure, use the following option:

seas(AirPassengers, x11 = list())
  
# Alternatively, all inputs may be entered manually, as in the following
# example:
    
seas(x = AirPassengers, 
     regression.variables = c("td1coef", "easter[1]", "ao1951.May"), 
     arima.model = "(0 1 1)(0 1 1)", regression.aictest = NULL,
     outlier = NULL, transform.function = "log")
  
# The 'static' command reveals the static call from above that is needed to
# replicate the automatic seasonal adjustment procedure:
    
static(m)
  
# invoke X-13ARIMA-SEATS options as 'spec.argument' through the ... argument:

# no test for easter effects
seas(AirPassengers, regression.aictest = c("td"))  

# force equality of annual values
seas(AirPassengers, force.type = "denton")  

# all series from X-13 can be extracted with series()
ts.plot(series(m, "forecast.forecasts"))

# use genhol to generate user defined holiday variables:
data(seasonal)  # exports and imports of China
data(holiday)  # dates of Chinese New Year and Easter
cny.ts <- genhol(cny, start = 0, end = 6, center = "calendar")

# the series can be used as a user defined regressor
plot(cny.ts)

seas(imp, xreg = cny.ts, regression.usertype = "holiday", x11 = list(),
     regression.variables = c("td1coef", "ls1985.Jan", "ls2008.Nov"),
     arima.model = "(0 1 2)(0 1 1)", regression.aictest = NULL,
     outlier = NULL, transform.function = "log")

# For many more examples, go to: 
# https://github.com/christophsax/seasonal/wiki/Examples-of-X-13ARIMA-SEATS-in-R

Try the seasonal package in your browser

Any scripts or data that you put into this service are public.

seasonal documentation built on May 30, 2017, 4:24 a.m.