Interactive analysis of gappy bivariate time series using AGSS
Authors
Lewis, Peter A. W.
Ray, Bonnie K.
Subjects
Time series; interpolation; bivariate
Advisors
Date of Issue
1992-06
Date
1992-06
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
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
Type
Technical Report
Description
Series/Report No
Department
Operations Research
Organization
Graduate School of Operational and Information Sciences (GSOIS)
Identifiers
NPS Report Number
NPS-OR-92-013
Sponsors
National Research Council
Funder
O&MN Direct Funding
Format
Citation
Distribution Statement
Approved for public release; distribution is unlimited.