Automatic trend estimation (SpringerBriefs in Physics)

Automatic trend estimation (SpringerBriefs in Physics)


Our ebook introduces a style to judge the accuracy of pattern estimation algorithms lower than stipulations just like these encountered in genuine time sequence processing. this technique relies on Monte Carlo experiments with synthetic time sequence numerically generated via an unique set of rules. the second one a part of the e-book comprises numerous computerized algorithms for pattern estimation and time sequence partitioning. The resource codes of the pc courses imposing those unique computerized algorithms are given within the appendix and may be freely on hand on the internet. The booklet comprises transparent assertion of the stipulations and the approximations below which the algorithms paintings, in addition to the right kind interpretation in their effects. We illustrate the functioning of the analyzed algorithms through processing time sequence from astrophysics, finance, biophysics, and paleoclimatology. The numerical test technique broadly utilized in our booklet is already in universal use in computational and statistical physics.

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