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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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The relationship between economic factors and equity markets in Central Europe
Jan Hanousek,Randall K. Filer +1 more
TL;DR: In this article, the authors investigated the possibility that newly emerging equity markets in Central Europe exhibit semi-strong form efficiency such that no relationship exists between lagged values of changes in economic variables and changes in equity prices.
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The gold‐silver spread: Integration, cointegration, predictability, and ex‐ante arbitrage
Journal ArticleDOI
Selection of the order of autoregressive models for spectral analysis of doppler ultrasound signals
TL;DR: It was found that, for more than 98% of the 1280 frames of Doppler signals analyzed, the order selected by the various criteria was ten or less, and overestimating the model order is better than underestimating it.
Book ChapterDOI
Nonlinear versus Linear Models in Functional Neuroimaging: Learning Curves and Generalization Crossover
Niels Mørch,Lars Kai Hansen,Stephen C. Strother,Claus Svarer,David A. Rottenberg,Benny Lautrup,Robert L. Savoy,Olaf B. Paulson +7 more
TL;DR: It is demonstrated that for sets of scans of two simple motor tasks—one set acquired with [O15]water using PET, and the other using fMRI—practical N's exist for which “generalization crossover” occurs, and this observation supports the application of highly flexible, ANN models to sufficiently large functional activation datasets.
Journal ArticleDOI
Inoculum type does not affect overall resistance of an arbuscular mycorrhiza-defective tomato mutant to colonisation but inoculation does change competitive interactions with wild-type tomato
TL;DR: It is concluded from the second experiment that mycorrhizal responsiveness is influenced by competition with a surrogate nonhost plant rmc in a situation that mimics interspecific competition, and is therefore a community-based parameter.
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