Interactive analysis of gappy bivariate time series using AGSS
By: Peter A. W. Lewis, and Bonnie Ray
Contributors: Ray, Bonnie K.; Naval Postgraduate School (U.S.). Dept. of Operations Research
Publisher: Naval Postgraduate School; Available from National Technical Information Service
Published: 1992
Place of publication: Monterey, Calif; Springfield, Va
Language: eng
Subjects: TIME SERIES ANALYSIS; BIVARIATE ANALYSIS; COMPUTER PROGRAMS
Other titles: NPS-OR-92-013.
Description: Bivariate time series which display nonstationary behavior, such as cycles or long-term trends,      are common in fields such as oceanography and meteorology. These are usually very      large-scale data sets and often may contain long gaps of missing values in one or both series,      with the gaps perhaps occurring at different time periods in the two series. We present a      simplified but effective method of interactively examining and filling in the missing values in such      series using extensions of the methods available in AGSS, an APL2-based statistical software      package. Our method allows for possible detrending and removal of seasonal components      before automatically estimating arbitrary patterns of missing values for each series. Interactive      bivariate spectral analysis can then be performed on the detrended and deseasonalized      interpolated data if desired. We illustrate our results using a bivariate time series of ocean      current velocities measured off the California coast. Time series; interpolation; bivariate.
Notes: Cover title.

"NPS-OR-92-013."

"June 1992."

AD A255 160.

Includes bibliographical references (p. 4-5).

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