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Univariate Time Series in Geosciences : Theory and Examples /

By: Gilgen, Hans [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006.Description: XVIII, 718 p. 220 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540309680.Subject(s): Earth sciences | Geophysics | Atmospheric sciences | Computer simulation | Physics | Earth Sciences | Geophysics/Geodesy | Earth Sciences, general | Atmospheric Sciences | Simulation and Modeling | Numerical and Computational Physics | Environmental Monitoring/AnalysisDDC classification: 550 | 526.1 Online resources: Click here to access online
Contents:
Stationary Stochastic Processes -- Linear Models for the Expectation Function -- Interpolation -- Linear Processes -- Fourier Transforms of Deterministic Functions -- Fourier Representation of a Stationary Stochastic Process -- Does a Periodogram Estimate a Spectrum? -- Estimators for a Continuous Spectrum -- Estimators for a Spectrum Having a Discrete Part.
In: Springer eBooksSummary: The author introduces the statistical analysis of geophysical time series. The book includes also a chapter with an introduction to geostatistics, many examples and exercises which help the reader to work with typical problems. More complex derivations are provided in appendix-like supplements to each chapter. Readers are assumed to have a basic grounding in statistics and analysis. The reader is invited to learn actively from genuine geophysical data. He has to consider the applicability of statistical methods, to propose, estimate, evaluate and compare statistical models, and to draw conclusions. The author focuses on the conceptual understanding. The example time series and the exercises lead the reader to explore the meaning of concepts such as the estimation of the linear time series (AMRA) models or spectra. This book is also a guide to using "R" for the statistical analysis of time series. "R" is a powerful environment for the statistical and graphical analysis of data."R" is available under GNU conditions.
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Item type Current location Call number Status Date due Barcode Item holds
E books E books PK Kelkar Library, IIT Kanpur
Available EBK4738
Total holds: 0

Stationary Stochastic Processes -- Linear Models for the Expectation Function -- Interpolation -- Linear Processes -- Fourier Transforms of Deterministic Functions -- Fourier Representation of a Stationary Stochastic Process -- Does a Periodogram Estimate a Spectrum? -- Estimators for a Continuous Spectrum -- Estimators for a Spectrum Having a Discrete Part.

The author introduces the statistical analysis of geophysical time series. The book includes also a chapter with an introduction to geostatistics, many examples and exercises which help the reader to work with typical problems. More complex derivations are provided in appendix-like supplements to each chapter. Readers are assumed to have a basic grounding in statistics and analysis. The reader is invited to learn actively from genuine geophysical data. He has to consider the applicability of statistical methods, to propose, estimate, evaluate and compare statistical models, and to draw conclusions. The author focuses on the conceptual understanding. The example time series and the exercises lead the reader to explore the meaning of concepts such as the estimation of the linear time series (AMRA) models or spectra. This book is also a guide to using "R" for the statistical analysis of time series. "R" is a powerful environment for the statistical and graphical analysis of data."R" is available under GNU conditions.

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