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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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Directional Coupling From the Olfactory Bulb to the Hippocampus During a Go/No-Go Odor Discrimination Task
TL;DR: Directional coherence (DCOH estimate) is provided, a method based on the temporal relation between two or more signals in the frequency domain, indicating that, during odor processing, beta oscillations in the hippocampus are driven by the olfactory bulb.
Journal ArticleDOI
Model Predictive Charging Control of In-Vehicle Batteries for Home Energy Management Based on Vehicle State Prediction
TL;DR: The harmonious combination of stochastic modeling/prediction and MPC in real-time home energy management system is one of the main contributions of this paper.
Journal ArticleDOI
The Fisher effect: new evidence and implications
Yasser A.F Fahmy,Magda Kandil +1 more
TL;DR: In this article, the authors show that the correlation between nominal interest rates and inflation rates increases with maturity until they move in a one-to-one relation at long horizon, which does not support the short run Fisher effect since short-term interest rates are associated with negligible changes in expected inflation.
Journal ArticleDOI
Managed futures, positive feedback trading, and futures price volatility
Scott H. Irwin,Satoko Yoshimaru +1 more
TL;DR: In this paper, the impact of commodity pool trading on futures price volatility was analyzed for the period 1 December 1988 through 31 March 1989 for 36 different futures markets, including the daily trading volume of large commodity pools.
Journal ArticleDOI
On generalization by neural networks
TL;DR: It is shown that a prescriptive learning procedure where the weights are simply read off based on the training data can provide good generalization.
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