Automatic trend estimation (SpringerBriefs in Physics)

Automatic trend estimation (SpringerBriefs in Physics)


Our booklet introduces a style to guage the accuracy of development estimation algorithms less than stipulations just like these encountered in genuine time sequence processing. this system is predicated on Monte Carlo experiments with synthetic time sequence numerically generated by way of an unique set of rules. the second one a part of the booklet includes numerous automated algorithms for pattern estimation and time sequence partitioning. The resource codes of the pc courses enforcing those unique computerized algorithms are given within the appendix and should be freely to be had on the internet. The ebook includes transparent assertion of the stipulations and the approximations less than which the algorithms paintings, in addition to the right kind interpretation in their effects. We illustrate the functioning of the analyzed algorithms via processing time sequence from astrophysics, finance, biophysics, and paleoclimatology. The numerical test approach broadly utilized in our ebook is already in universal use in computational and statistical physics.

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