Singular spectrum analysis for time series with missing data

Geophysical Research Letters
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Abstract

Geophysical time series often contain missing data, which prevents analysis with many signal processing and multivariate tools. A modification of singular spectrum analysis for time series with missing data is developed and successfully tested with synthetic and actual incomplete time series of suspended-sediment concentration from San Francisco Bay. This method also can be used to low pass filter incomplete time series.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Singular spectrum analysis for time series with missing data
Series title Geophysical Research Letters
DOI 10.1029/2000GL012698
Volume 28
Issue 16
Year Published 2001
Language English
Contributing office(s) Pacific Regional Director's Office, San Francisco Bay-Delta
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Geophysical Research Letters
First page 3187
Last page 3190
Online Only (Y/N) N
Additional Online Files (Y/N) N