Climate time series analysis: classical statistical and bootstrap methods
Climate is a paradigm of a complex system. Analysing climate data is an exciting challenge, which is increased by non-normal distributional shape, serial dependence, uneven spacing and timescale uncertainties. This book presents bootstrap resampling as a computing-intensive method able to meet the challenge. It shows the bootstrap to perform reliably in the most important statistical estimation techniques: regression, spectral analysis, extreme values and correlation. This book is written for c…
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- Full title :Climate time series analysis : classical statistical and bootstrap methods / Manfred Mudelsee.
Summary
Climate is a paradigm of a complex system. Analysing climate data is an exciting challenge, which is increased by non-normal distributional shape, serial dependence, uneven spacing and timescale uncertainties. This book presents bootstrap resampling as a computing-intensive method able to meet the challenge. It shows the bootstrap to perform reliably in the most important statistical estimation techniques: regression, spectral analysis, extreme values and correlation. This book is written for climatologists and applied statisticians. It explains step by step the bootstrap algorithms (including.
Read More ↓Edition Statements
- Publication Date:©2010.
Publication Statements
- Publisher(s):Springer
- Place of Publication:Dordrecht
- Language:eng
- Publication Date:©2010.
The Physical Object
- Description:1 online resource (xxxiv, 474 pages) : : illustrations
Edition Identifiers
- ISBN:9789048194827, 9048194822
- DOI:10.1007/978-90-481-9482-7
- oclc:ocn676700962
- LC Classification:QC981
- Dewey Decimal:551.6072/7
Table of Contents
Preface; Acknowledgements; List of Algorithms; List of Figures; List of Tables; Part I Fundamental Concepts; 1. Introduction; 2. Persistence Models; 3. Bootstrap Confidence Intervals; Part II Univariate Time Series; 4. Regression I; 5. Spectral Analysis; 6. Extreme Value Time Series; Part III Bivariate Time Series; 7. Correlation; 8. Regression II; Part IV Outlook; 9. Future Directions; References; Subject Index; Author Index.
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