U.S. Department of Commerce

Research Reports

You are here: Census.gov › Subjects A to Z › Research Reports Sorted by Year › Abstract of RRS2008/01
Skip top of page navigation

A Nonlinear Algorithm for Seasonal Adjustment in Multiplicative Component Decompositions

Tucker McElroy

KEY WORDS: Nonstationary time series, Seasonality, Trends

ABSTRACT

We propose a new model-based, nonlinear method for seasonally adjusting time series in a multiplicative components model. The method seeks to reduce the bias inherent in linear model- based approaches, while at the same time preserving the °exibility of parametric methods. We discuss the problem of bias and the concept of recovery, and demonstrate the favorable properties of the proposed algorithm on several synthetic series.

CITATION:

Source: U.S. Census Bureau, Statistical Research Division

Created: February 21, 2008
Last revised: February 21, 2008


[PDF] or PDF denotes a file in Adobe’s Portable Document Format. To view the file, you will need the Adobe® Reader® Off Site available free from Adobe.

This symbol Off Site indicates a link to a non-government web site. Our linking to these sites does not constitute an endorsement of any products, services or the information found on them. Once you link to another site you are subject to the policies of the new site.

Source: U.S. Census Bureau | Statistical Research Division | (301) 763-3215 (or chad.eric.russell@census.gov) |   Last Revised: October 08, 2010