Time-series analysis is about the study of data collected through time. The field of time series is a vast one that pervades many areas of science and engineering, particularly statistics and signal processing: this short paper can only be an advertisement.
Hence, the first thing to note is that there are several excellent texts on time-series analysis. Most statistical books concentrate on stationary time series and some texts have good coverage of ‘globally non-stationary’ series such as those often used in financial time series. For a general, elementary introduction to time-series analysis the author highly recommends the book by Chatfield (2003). The core of Chatfield’s book is a highly readable account of various topics in time-series including time-series models, forecasting, time series in the frequency domain and spectrum estimation, and also linear systems. More recent editions contain useful, well-presented and well-referenced information on important new research areas. Of course, there are many other books: ones the author finds useful are those by Priestley (1983), Diggle (1990), Brockwell & Davis (1991) and Hamilton (1994). The book by Hannan (1960) is concise (but concentrated) and that by Pole et al. (1994) is a good introduction to a Bayesian way of doing time-series analysis. There are undoubtedly many more books.This paper is a brief survey of several kinds of time-series model and analysis. The ï—rst section covers stationary time series, which, loosely speaking, are those whose statistical properties
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Statistics in Volcanology
Statistics in Volcanology is a comprehensive guide to modern statistical methods applied in volcanology written by today's leading authorities. The volume aims to show how the statistical analysis of complex volcanological data sets, including time series, and numerical models of volcanic processes can improve our ability to forecast volcanic eruptions. Specific topics include the use of expert elicitation and Bayesian methods in eruption forecasting, statistical models of temporal and spatial patterns of volcanic activity, analysis of time series in volcano seismology, probabilistic hazard assessment, and assessment of numerical models using robust statistical methods. Also provided are comprehensive overviews of volcanic phenomena, and a full glossary of both volcanological and statistical terms.
Statistics in Volcanology is essential reading for advanced undergraduates, graduate students, and research scientists interested in this multidisciplinary field.