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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.
Climate Time Series Analysis 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. It explains step by step the bootstrap algorithms (including novel adaptions) and methods for confidence interval construction and tests the accuracy of the algorithms by means of Monte Carlo experiments.
- Fundamental Concepts
- Persistence Models
- Bootstrap Confidence Intervals
- Univariate Time Series
- Regression I
- Spectral Analysis
- Extreme Value Time Series
- Bivariate Time Series
- Regression II
- Future Directions
Manfred Mudelsee received his diploma in Physics from the University of Heidelberg and his doctoral degree in Geology from the University of Kiel.