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Outliers, level shifts, and variance changes in time series
Author(s) -
Tsay Ruey S.
Publication year - 1988
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.3980070102
Subject(s) - outlier , univariate , variance (accounting) , series (stratigraphy) , simple (philosophy) , residual , statistics , econometrics , computer science , time series , mathematics , algorithm , multivariate statistics , paleontology , philosophy , accounting , epistemology , business , biology
Outliers, level shifts, and variance changes are commonplace in applied time series analysis. However, their existence is often ignored and their impact is overlooked, for the lack of simple and useful methods to detect and handle those extraordinary events. The problem of detecting outliers, level shifts, and variance changes in a univariate time series is considered. The methods employed are extremely simple yet useful. Only the least squares techniques and residual variance ratios are used. The effectiveness of these simple methods is demonstrated by analysing three real data sets.