Automatic trend estimation (Paperback, 2013 ed.)

Our book introduces a method to evaluate the accuracy of trend estimation algorithms under conditions similar to those encountered in real time series processing. This method is based on Monte Carlo experiments with artificial time series numerically generated by an original algorithm. The second part of the book contains several automatic algorithms for trend estimation and time series partitioning. The source codes of the computer programs implementing these original automatic algorithms are given in the appendix and will be freely available on the web. The book contains clear statement of the conditions and the approximations under which the algorithms work, as well as the proper interpretation of their results. We illustrate the functioning of the analyzed algorithms by processing time series from astrophysics, finance, biophysics, and paleoclimatology. The numerical experiment method extensively used in our book is already in common use in computational and statistical physics.

General

Imprint:	Springer
Country of origin:	Netherlands
Series:	SpringerBriefs in Physics
Release date:	September 2012
First published:	2013
Authors:	Calin Vamos • Maria Craciun
Dimensions:	235 x 155 x 7mm (L x W x T)
Format:	Paperback
Pages:	131
Edition:	2013 ed.
ISBN-13:	978-9400748248
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Computing & IT > Applications of computing > Computer modelling & simulation Books > Science & Mathematics > Mathematics > Applied mathematics > General Books > Science & Mathematics > Physics > Thermodynamics & statistical physics > Statistical physics Books > Computing & IT > Computer software packages > Computer graphics software > General Promotions
LSN:	9400748248
Barcode:	9789400748248

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