seasonal v1.7.0


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R Interface to X-13-ARIMA-SEATS

Easy-to-use interface to X-13-ARIMA-SEATS, the seasonal adjustment software by the US Census Bureau. It offers full access to almost all options and outputs of X-13, including X-11 and SEATS, automatic ARIMA model search, outlier detection and support for user defined holiday variables, such as Chinese New Year or Indian Diwali. A graphical user interface can be used through the 'seasonalview' package. Uses the X-13-binaries from the 'x13binary' package.


R interface to X-13ARIMA-SEATS

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seasonal is an easy-to-use and full-featured R-interface to X-13ARIMA-SEATS, the newest seasonal adjustment software developed by the United States Census Bureau.


seasonal depends on the x13binary package to access pre-built binaries of X-13ARIMA-SEATS on all platforms and does not require any manual installation. To install both packages:


Getting started

seas is 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)

For a more detailed introduction, check our article in the Journal of Statistical Software or consider the vignette:



In seasonal, it is possible to use almost the complete syntax of X-13ARIMA-SEATS. The X-13ARIMA-SEATS syntax uses specs and arguments, with each spec optionally containing some arguments. These spec-argument combinations can be added to seas by separating the spec and the argument by a dot (.). For example, in order to set the 'variables' argument of the 'regression' spec equal to td and ao1999.jan, the input to seas looks like this:

m <- seas(AirPassengers, regression.variables = c("td", "ao1955.jan"))

The best way to learn about the relationship between the syntax of X-13ARIMA-SEATS and seasonal is to study the comprehensive list of examples. Detailed information on the options can be found in the Census Bureaus' official manual.


seasonal has a flexible mechanism to read data from X-13ARIMA-SEATS. With the series function, it is possible to import almost all output that can be generated by X-13ARIMA-SEATS. For example, the following command returns the forecasts of the ARIMA model as a "ts" time series:

m <- seas(AirPassengers)
series(m, "forecast.forecasts")


There are several graphical tools to analyze a seas model. The main plot function draws the seasonally adjusted and unadjusted series, as well as the outliers:

m <- seas(AirPassengers, regression.aictest = c("td", "easter"))

Graphical User Interface

The view function is a graphical tool for choosing a seasonal adjustment model, using the seasonalview package, with the same structure as the demo website of seasonal. To install seasonalview, type:


The goal of view is to summarize all relevant options, plots and statistics that should be usually considered. view uses a "seas" object as its main argument:



seasonal is free and open source, licensed under GPL-3. It requires the X-13ARIMA-SEATS software by the U.S. Census Bureau, which is open source and freely available under the terms of its own license.

To cite seasonal in publications use:

Sax C, Eddelbuettel D (2018). “Seasonal Adjustment by X-13ARIMA-SEATS in R.” Journal of Statistical Software, 87(11), 1-17. doi: 10.18637/jss.v087.i11 (URL:

Please report bugs and suggestions on Github. Thank you!

Functions in seasonal

Name Description
checkX13 Check Installation of X-13ARIMA-SEATS
predict.seas Seasonal Adjusted Series
final Time Series of a Seasonal Adjustment Model
fivebestmdl Five Best ARIMA Models Coerce Output to data.frame
SPECS List of Available X-13ARIMA-SEATS Outputs
seas Seasonal Adjustment with X-13ARIMA-SEATS
arimamodel Defunct Functions
out Display X-13ARIMA-SEATS Output
outlier Outlier Time series
easter Dates of Chinese New Year, Indian Diwali and Easter
udg Diagnostical Statistics
unemp United States Unemployment Level
import.ts Import Time Series from X-13 Data Files
exp Exports and Imports of China
iip Industrial Production of India
update.seas Update and Re-evaluate a Seasonal Adjustment Model
na.x13 Handle Missing Values by X-13
view Interactively Modify a Seasonal Adjustment Model
import.spc Import X-13 .spc Files
seasonal-package seasonal: R interface to X-13ARIMA-SEATS
genhol Generate Holiday Regression Variables
series Import X-13ARIMA-SEATS Output Tables
identify.seas Manually Identify Outliers
summary.seas Summary of a X13-ARIMA-SEATS seasonal adjustment
spc .spc File Content
static Static Call of a seas Object
transformfunction Applied Transformation
cpi Consumer Price Index of Switzerland
plot.seas Seasonal Adjustment Plots
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Vignettes of seasonal

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Type Package
Date 2018-12-20
License GPL-3
LazyData true
RoxygenNote 6.1.1
Encoding UTF-8
NeedsCompilation no
Packaged 2018-12-20 07:40:19 UTC; christoph
Repository CRAN
Date/Publication 2018-12-20 10:30:03 UTC

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