Titlebook: Climate Time Series Analysis; Classical Statistica Manfred Mudelsee Book 2014Latest edition Springer International Publishing Switzerland 2

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Vereinigung der GrosskesselbesitzerKuhn, The Structure of Scientific Revolutions, 2nd edn. University of Chicago Press, Chicago, 210 pp, 1970), extensions of previous material (Chaps. .–.). Then we take a chance (Sects. 9.4 and 9.5) and look on paradigm changes in climate data analysis that may be effected by virtue of strongly incre

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Book 2014Latest editionhematical and statistical summary of time-series analysis techniques geared towards climate applications…accessible to readers with knowledge of college-level calculus and statistics..” (Computers and Geosciences).“.A key part of the book that separates it from other time series works is the explici

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ProVoet onder begeleiding van het CBOthin the geological past..Man observes nature and climate to learn, or extract information, and to predict. Since the climate system is complex and not all variables can be observed at arbitrary spatial and temporal range and resolution, our knowledge is, and shall be, restricted and uncertainty is

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ProVoet onder begeleiding van het CBOence models with a unique correspondence to continuous-time models is rather limited. This “embedding” is necessary because it guarantees that our persistence description has a foundation on physics. The first-order autoregressive or AR(1) process has this desirable property.

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Richtlijnen behandeling van voetenmate changes: their size and timing. For that aim, the ramp regression (Sect. 4.2.1) constitutes a useful parametric model of climate changes..We compare the bootstrap with the classical approach to determine error bars and CIs for estimated regression parameters. The difficulties imposed by the dat

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Richtlijnen behandeling van voetenhe time domain and avoids distortions caused by interpolation..Bootstrap resampling enhances multitaperand Lomb–Scarglemethods by providing a bias correctionand CIs. It supplies also a detection testfor a spectral peak against realistic noise alternatives in the form of an AR(1)process (“red noise”)