Climate time series analysis

Climate time series analysis: classical statistical and bootstrap methods

by Mudelsee, Manfred

Type Book
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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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Title Statements

  • 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.

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Edition Statements

  • Publication Date:©2010.

Publication Statements

  • Publisher(s):Springer
  • Place of Publication:Dordrecht
  • Language:eng
  • Publication Date:©2010.

Notes

Print version record.

The Physical Object

  • Description:1 online resource (xxxiv, 474 pages) : : ilustr.

Edition Identifiers

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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