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.
Suggested Citation
Schoellhamer, D., 2001, Singular spectrum analysis for time series with missing data: Geophysical Research Letters, v. 28, no. 16, p. 3187-3190, https://doi.org/10.1029/2000GL012698.
| 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 |
| Publication Date | August 15, 2001 |
| Year Published | 2001 |
| Language | English |
| Contributing office(s) | San Francisco Bay-Delta, Pacific Regional Director's Office |
| 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 |