,Angelika and Seasonal Adjustment with the R 1. Statistics ... · Kowarik1,Angelika Meraner1 and Matthias Templ1,2 1. Statistics Austria 2. Vienna University of Technology useR 2015

S T A T I S T I K A U S T R I A

D i e I n f o r m a t i o n s m a n a g e r

AlexanderKowarik1,Angelika

Meraner1 andMatthias Templ1,2

1. Statistics Austria

2. Vienna University of

Technology

useR 2015

Aalborg, July 2015

Seasonal Adjustment with the R

packages x12 and x12GUI

Kowarik, Meraner, Templ (STAT, TU) 1 / 20 | Aalborg, 2015



Motivation

I X12-ARIMA is widely used and state-of-the-art in many statisticalo�ces

I Statistical o�ces (we) have to apply seasonal adjustment frequentlyand to many di↵erent time series

I Graphical analysis should always be included in the process

I Results should be reproducable and easy to modify

I (X-13-ARIMA-SEATS is the successor if X12-ARIMA, SEATS notyet implemented)

≠æ R-packages x12 and x12GUI




Features

I Access to X12-ARIMA directly from within R (no spc, out, . . . files)

I Class oriented command line interface

I Change tracking for the X12-ARIMA parameters and output

I Batch processing of multiple time series at once (in parallel)

I Easy generation of graphical output

I Import the parameter settings from spc files to R




Class x12Single

Objects of class x12Single contain the following information

I ts - The original time serie

I x12Parameter - The current X12-ARIMA parameter setting

I x12Output - The current X12-ARIMA results

I x12OldParameter - All previous X12-ARIMA parameter settings

I x12OldOutput - All previous X12-ARIMA results




Methods x12Single

Methods for this class are:

I x12 - (Re)Run X12-ARIMA

I setP,getP - Change/View parameters

I prev,cleanHistory - Revert to a previous X12 parameter settingand output

I plot,plotRsdAcf,plotSpec,plotSeasFac - Plot methods

s <- new("x12Single", ts = AirPassengers ,tsName = "air")

s <- x12(s)forecast <- s@x12Output@forecast




Class x12Batch

Objects of class x12Batch

I Combination of multiple objects of class x12Single

I Inherit the methods from class x12Single

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

xb <- setP(xb, list(estimate = TRUE ,outlier.types = "all")

xb <- setP(xb, list(outlier.types = "LS", index =1)#options(x12.parallel =2)xb <- x12(xb)




Real example Batch - Tourism

> dat <- read.csv2("http://bit.ly/1RTF31S")

> tsObject <- lapply(split(dat[,5], list(dat[,2], dat[,3])),

+ # by state and country of origin

+ ts,start = c(1973,11), frequency = 12)

> length(tsObject)

[1] 774

> xb <- new("x12Batch", tsObject[1:3])

> xb <- setP(xb,list(forecast_years=3))

The parameters for all objects are changed.

> xb <- x12(xb)

Time difference of 6.766999 secs




Real example Batch - Tourism

> plot(xb@x12List[[1]], forecast = TRUE,

+ span = c(2008,4,2018,4), ylab = "Nights spend")

Time Series with Forecasts

Date

Nig

hts

spen

d

3000

050

000

7000

0

2008.1 2010.1 2012.1 2014.1 2016.1 2018.1




Plot functions I

I Output of the plot() method showing trend and forecasts withprediction intervals as well as the seasonally adjusted series.

Time Series with Forecasts

Date

Valu

e

100

200

300

400

500

600

700

1950.1 1952.1 1954.1 1956.1 1958.1 1960.1 1962.1

Original Seasonally Adjusted Trend




Plot functions II

I Output of the plotRsdAcf() function from the R package x12,showing the autocorrelations of the squared residuals from theregARIMA model.

2 4 6 8 10 12

−0.2

−0.1

0.0

0.1

0.2

Autocorrelations of the Squared Residuals

Lag

ACF




Plot functions III

I Output of the plotSpec() function, showing the spectrum of theseasonally adjusted series.

0.0 0.1 0.2 0.3 0.4 0.5

−40

−35

−30

Spectrum of the Seasonally Adjusted Series

Frequency

Dec

ibel

s

Spectrum Seasonal Frequencies Trading Day Frequencies




Plot functions IV

I Output of the seasonal factor plot (plotSeasFac()).

0.8

0.9

1.0

1.1

1.2

1.3

Seasonal Factors by period and SI Ratios

Valu

e

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

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Seasonal FactorsMean

SI RatioReplaced SI Ratio




Plot functions V

I Output of the plot() method showing outliers in the RegARIMAmodel.

Original Series and Trend

Date

Value

1950 1952 1954 1956 1958 1960

100

200

300

400

500

600

OriginalAO

TrendLS TC




Features x12GUI

I Overview of all (implemented) X12-ARIMA parameters

I Interactive adjustment of the parameters

I Interactive graphics

I Visualisation of the automatically detected outliers

I Easy addition, removal of manually selected outliers




Main View x12GUI

> xbn <- x12GUI(xb)




Main View x12GUI




Graphics x12GUI




Interactive Plots x12GUI I




Interactive Plots x12GUI II




Details and contact

I JSS paper“Seasonal Adjustment with the R packages x12 andx12GUI”

I Contact: Alexander Kowarik [email protected]

I https://github.com/alexkowa/x12


https://github.com/alexkowa/x12

Documents

,Angelika and Seasonal Adjustment with the R 1. Statistics ... · Kowarik1,Angelika Meraner1 and Matthias Templ1,2 1. Statistics Austria 2. Vienna University of Technology useR 2015