TY - BOOK ID - 8358905 TI - Climate time series analysis : classical statistical and bootstrap methods PY - 2010 SN - 9048194814 9786613002266 9048194822 1283002264 PB - Dordrecht : Springer Science+Business Media B.V., DB - UniCat KW - Climatic changes -- Statistical methods. KW - Climatology -- Statistical methods. KW - Tidsrekkeanalyse KW - Statistiske metoder KW - Geovitenskap KW - Geofysikk KW - Climatology KW - Time-series analysis KW - Meteorology & Climatology KW - Earth & Environmental Sciences KW - Statistical methods KW - Time-series analysis. KW - Statistical methods. KW - Analysis of time series KW - Environment. KW - Meteorology. KW - Statistics. KW - Climate change. KW - Climate Change. KW - Statistical Theory and Methods. KW - Autocorrelation (Statistics) KW - Harmonic analysis KW - Mathematical statistics KW - Probabilities KW - Climatic changes. KW - Mathematical statistics. KW - Mathematics KW - Statistical inference KW - Statistics, Mathematical KW - Statistics KW - Sampling (Statistics) KW - Changes, Climatic KW - Changes in climate KW - Climate change KW - Climate change science KW - Climate changes KW - Climate variations KW - Climatic change KW - Climatic changes KW - Climatic fluctuations KW - Climatic variations KW - Global climate changes KW - Global climatic changes KW - Climate change mitigation KW - Teleconnections (Climatology) KW - Environmental aspects KW - StatisticsĀ . KW - Statistical analysis KW - Statistical data KW - Statistical science KW - Econometrics KW - Aerology KW - Atmospheric science KW - Global environmental change UR - https://www.unicat.be/uniCat?func=search&query=sysid:8358905 AB - 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 novel adaptions) and methods for confidence interval construction. It tests the accuracy of the algorithms by means of Monte Carlo experiments. It analyses a large array of climate time series, giving a detailed account on the data and the associated climatological questions. This makes the book self-contained for graduate students and researchers. Manfred Mudelsee received his diploma in Physics from the University of Heidelberg and his doctoral degree in Geology from the University of Kiel. He was then postdoc in Statistics at the University of Kent at Canterbury, research scientist in Meteorology at the University of Leipzig and visiting scholar in Earth Sciences at Boston University; currently he does climate research at the Alfred Wegener Institute for Polar and Marine Research, Bremerhaven. His science focuses on climate extremes, time series analysis and mathematical simulation methods. He has authored over 50 peer-reviewed articles. In his 2003 Nature paper, Mudelsee introduced the bootstrap method to flood risk analysis. In 2005, he founded the company Climate Risk Analysis. ER -