| Nonstationarities in Hydrologic and Environmental Time Series 2003 Edition Contributor(s): Rao, A. R. (Author), Hamed, K. H. (Author), Huey-Long Chen (Author) |
|
 |
ISBN: 1402012977 ISBN-13: 9781402012976 Publisher: Springer OUR PRICE: $161.49 Product Type: Hardcover - Other Formats Published: July 2003 Annotation: Most of the time series analysis methods applied today rely heavily on the key assumptions of linearity, Gaussianity and stationarity. Natural time series, including hydrologic, climatic and environmental time series, which satisfy these assumptions seem to be the exception rather than the rule. Nevertheless, most time series analysis is performed using standard methods after relaxing the required conditions one way or another, in the hope that the departure from these assumptions is not large enough to affect the result of the analysis. A large amount of data is available today after almost a century of intensive data collection of various natural time series. In addition to a few older data series such as sunspot numbers, sea surface temperatures, etc., data obtained through dating techniques (tree-ring data, ice core data, geological and marine deposits, etc.), are available. With the advent of powerful computers, the use of simplified methods can no longer be justified, especially with the success of these methods in explaining the inherent variability in natural time series. This book presents a number of new techniques that have been discussed in the literature during the last two decades concerning the investigation of stationarity, linearity and Gaussianity of hydrologic and environmental times series. These techniques cover different approaches for assessing nonstationarity, ranging from time domain analysis, to frequency domain analysis, to the combined time-frequency and time-scale analyses, to segmentation analysis, in addition to formal statistical tests of linearity and Gaussianity. It is hoped that this endeavor would facilitate further research into this important area. |
| Additional Information |
| BISAC Categories: - Science | Earth Sciences - Hydrology - Mathematics | Applied - Mathematics | Probability & Statistics - General |
| Dewey: 003.3 |
| LCCN: 2003048859 |
| Series: Water Science and Technology Library |
| Physical Information: 0.87" H x 7.04" W x 9.2" (1.83 lbs) 365 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: Conventionally, time series have been studied either in the time domain or the frequency domain. The representation of a signal in the time domain is localized in time, i.e . the value of the signal at each instant in time is well defined . However, the time representation of a signal is poorly localized in frequency, i.e. little information about the frequency content of the signal at a certain frequency can be known by looking at the signal in the time domain . On the other hand, the representation of a signal in the frequency domain is well localized in frequency, but is poorly localized in time, and as a consequence it is impossible to tell when certain events occurred in time. In studying stationary or conditionally stationary processes with mixed spectra, the separate use of time domain and frequency domain analyses is sufficient to reveal the structure of the process . Results discussed in the previous chapters suggest that the time series analyzed in this book are conditionally stationary processes with mixed spectra. Additionally, there is some indication of nonstationarity, especially in longer time series. |