£72.95

About as cheap as it gets — within 5% of the all-time low it hit 1 month ago.

£73 today · all-time low £73 (Sep 2026) · usually the usual

Springer Multiscale Forecasting Models

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£74.83 £72.47 £72.98 £73.50 £74.01 £74.53 £75.05 28 July 2026 11 August 2026 25 August 2026 08 September 2026 22 September 2026
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Most common price: £74 (30 days, 52.6%)

Price range: £73 - £75

Price levels: 3 different prices over 57 days

Description

This book presents two new decomposition methods to decompose a time series in intrinsic components of low and high frequencies. The methods are based on Singular Value Decomposition (SVD) of a Hankel matrix (HSVD). The proposed decomposition is used to improve the accuracy of linear and nonlinear auto-regressive models. Linear Auto-regressive models (AR, ARMA and ARIMA) and Auto-regressive Neural Networks (ANNs) have been found insufficient because of the highly complicated nature of some time series. Hybrid models are a recent solution to deal with non-stationary processes which combine pre-processing techniques with conventional forecasters, some pre-processing techniques broadly implemented are Singular Spectrum Analysis (SSA) and Stationary Wavelet Transform (SWT). Although the flexibility of SSA and SWT allows their usage in a wide range of forecast problems, there is a lack of standard methods to select their parameters. The proposed decomposition HSVD and Multilevel SVD are described in detail through time series coming from the transport and fishery sectors. Further, for comparison purposes, it is evaluated the forecast accuracy reached by SSA and SWT, both jointly with AR-based models and ANNs.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
03 January 2019
Listed Since
03 January 2019

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No barcode data available

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