seasonal v1.7.1


Monthly downloads



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

Build Status Build status Downloads

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
identify.seas Manually Identify Outliers
predict.seas Seasonal Adjusted Series
view Interactively Modify a Seasonal Adjustment Model
update.seas Update and Re-evaluate a Seasonal Adjustment Model
plot.seas Seasonal Adjustment Plots
na.x13 Handle Missing Values by X-13
static Static Call of a seas Object
import.ts Import Time Series from X-13 Data Files
out Display X-13ARIMA-SEATS Output
seas Seasonal Adjustment with X-13ARIMA-SEATS
spc .spc File Content
arimamodel Defunct Functions
seasonal-package seasonal: R interface to X-13ARIMA-SEATS
import.spc Import X-13 .spc Files
series Import X-13ARIMA-SEATS Output Tables
outlier Outlier Time series
iip Industrial Production of India
udg Diagnostical Statistics
summary.seas Summary of a X13-ARIMA-SEATS seasonal adjustment
transformfunction Applied Transformation
unemp United States Unemployment Level
easter Dates of Chinese New Year, Indian Diwali and Easter
checkX13 Check Installation of X-13ARIMA-SEATS
genhol Generate Holiday Regression Variables Coerce Output to data.frame
SPECS List of Available X-13ARIMA-SEATS Outputs
final Time Series of a Seasonal Adjustment Model
exp Exports and Imports of China
cpi Consumer Price Index of Switzerland
fivebestmdl Five Best ARIMA Models
No Results!

Vignettes of seasonal

No Results!

Last month downloads


Type Package
Date 2020-06-06
License GPL-3
LazyData true
RoxygenNote 7.1.0
Encoding UTF-8
NeedsCompilation no
Packaged 2020-06-06 09:30:43 UTC; christoph
Repository CRAN
Date/Publication 2020-06-06 10:10:02 UTC

Include our badge in your README