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Analysis of time series is part of statistical analysis concerning data which consecutively appear in time, space or both. Examples of such series of data are the daily price of stocks, monthly rainfall in a certain location, hourly blood pressure of a patient, etc. In this book, methods are presented for finding the probabilistic rules governing the series and predicting their future values with some dgrees of uncertainty.
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Bibliography: p. 105.
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- Created April 1, 2008
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September 27, 2020 | Edited by MARC Bot | import existing book |
December 14, 2009 | Edited by WorkBot | link works |
April 1, 2008 | Created by an anonymous user | Imported from Scriblio MARC record |