Principles of Neural Model Identification Selection and Adequacy is popular PDF and ePub book, written by Achilleas Zapranis in 2012-12-06, it is a fantastic choice for those who relish reading online the Computers genre. Let's immerse ourselves in this engaging Computers book by exploring the summary and details provided below. Remember, Principles of Neural Model Identification Selection and Adequacy can be Read Online from any device for your convenience.
Principles of Neural Model Identification Selection and Adequacy Book PDF Summary
Neural networks have had considerable success in a variety of disciplines including engineering, control, and financial modelling. However a major weakness is the lack of established procedures for testing mis-specified models and the statistical significance of the various parameters which have been estimated. This is particularly important in the majority of financial applications where the data generating processes are dominantly stochastic and only partially deterministic. Based on the latest, most significant developments in estimation theory, model selection and the theory of mis-specified models, this volume develops neural networks into an advanced financial econometrics tool for non-parametric modelling. It provides the theoretical framework required, and displays the efficient use of neural networks for modelling complex financial phenomena. Unlike most other books in this area, this one treats neural networks as statistical devices for non-linear, non-parametric regression analysis.
Detail Book of Principles of Neural Model Identification Selection and Adequacy PDF
- Author : Achilleas Zapranis
- Release : 06 December 2012
- Publisher : Springer Science & Business Media
- ISBN : 9781447105596
- Genre : Computers
- Total Page : 194 pages
- Language : English
- PDF File Size : 13,6 Mb
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