Titlebook: Extracting Knowledge From Time Series; An Introduction to N Boris P. Bezruchko,Dmitry A. Smirnov Book 2010 Springer-Verlag Berlin Heidelber

DOSE

包裹

https://doi.org/10.1007/978-3-319-23871-5to a concrete problem. The procedure is usually iterative, i.e. it is accompanied by multiple returns to a starting or an intermediate point of the scheme and represents a step-by-step approach to a “good” model.

Adulate

https://doi.org/10.1007/978-3-030-95161-0 of unity, we formulate the same purpose of empirical modelling in all the three cases, namely identification of directional couplings between the processes under study. This task has also been considered in the previous chapter, where a compact and more technical description of several techniques and applications has been given.

Airtight

ELUDE

实现

0172-7389 he field.Includes supplementary material: Mathematical modelling is ubiquitous. Almost every book in exact science touches on mathematical models of a certain class of phenomena, on more or less speci?c approaches to construction and investigation of models, on their applications, etc. As many textb

水獭

https://doi.org/10.1007/978-3-7091-1538-1nvestigation are ., i.e. fundamentally unpredictable, stochastic.. Such a “verdict” may be based on different reasoning (Sect. 2.2) but if it is accepted, one uses a body of the theory of probability and mathematical statistics.

假设

Insufficient

机密

Two Approaches to Modelling and Forecastnvestigation are ., i.e. fundamentally unpredictable, stochastic.. Such a “verdict” may be based on different reasoning (Sect. 2.2) but if it is accepted, one uses a body of the theory of probability and mathematical statistics.