Book ChapterDOI
Fitting autoregressive models for prediction
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This is a preliminary report on a newly developed simple and practical procedure of statistical identification of predictors by using autoregressive models in a stationary time series.Abstract:
This is a preliminary report on a newly developed simple and practical procedure of statistical identification of predictors by using autoregressive models. The use of autoregressive representation of a stationary time series (or the innovations approach) in the analysis of time series has recently been attracting attentions of many research workers and it is expected that this time domain approach will give answers to many problems, such as the identification of noisy feedback systems, which could not be solved by the direct application of frequency domain approach [1], [2], [3], [9].read more
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Rule generation for hierarchical collaborative fuzzy system
TL;DR: An association process of different fuzzy systems is presented in this work, through the use of a relevance concept of a fuzzy system, which results in a collaborative structure where all sub-models have the ability to gradually improve the overall accuracy of approximation by adding their own contributions.
Book ChapterDOI
Semi-empirical modeling of non-linear dynamic systems through identification of operating regimes and local models
Tor Arne Johansen,Bjarne A. Foss +1 more
TL;DR: An off-line algorithm for semi-empirical modeling of nonlinear dynamic systems is presented, based on a number of simple local models, where the validity of each local model is restricted to an operating regime, but where the local models yield a complete global model when interpolated.
Journal ArticleDOI
A Dialogue Concerning a New Instrument for Econometric Modeling
TL;DR: This paper presents a set of questions prepared by Clive Granger with responses by David Hendry on the use of PcGets (see Hendry and Krolzig, 2001) in data modeling and as a new research tool.
Proceedings ArticleDOI
Hybrid Deep Sequential Modeling for Social Text-Driven Stock Prediction
TL;DR: A novel Cross-modal attention based Hybrid Recurrent Neural Network (CH-RNN), inspired by the recent proposed DA-Rnn model, which is effective and benefit of considering social texts is demonstrated.
The Relationship Between Exchange Rates and Stock Prices: A Causality Analysis
TL;DR: The authors analyzes empirically the relationship between stock prices and exchange rates by using high-frequency data of exchange rates and aggregate stock indices of Turkey and provides evidence that a long-run stable relationship exists only from exchange rate to industry sector index.
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