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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Journal ArticleDOI
Comparison of quantitative structure-activity relationship model performances on carboquinone derivatives.
TL;DR: The MDFV model proved to be the best model for the considered carboquinone derivatives according to the defined information and prediction criteria, Kubinyi function, and Akaike's weights.
Journal ArticleDOI
Financial interdependence between Hong Kong and the US: A band spectrum approach
TL;DR: In this article, a causal relationship between Hong Kong and US financial markets, using band spectrum regression techniques that allow us to examine the dynamic properties of the interactions between capital markets, is studied.
Proceedings ArticleDOI
Coordination and Trajectory Prediction for Vehicle Interactions via Bayesian Generative Modeling
TL;DR: In this paper, a coordination and trajectory prediction system (CTPS) is proposed, which has a hierarchical structure including a macro-level coordination recognition module and a micro-level subtle pattern prediction module which solves a probabilistic generation task.
Journal ArticleDOI
Nonparametric estimation of a periodic sequence in the presence of a smooth trend
Michael Vogt,Oliver Linton +1 more
TL;DR: In this article, a nonparametric regression model including a periodic component, a smooth trend function, and a stochastic error term is proposed to estimate the unknown period and the function values of the periodic component.
Journal ArticleDOI
Maximum entropy spectral analysis of 31P NMR signals from human cells
TL;DR: In this article, two autoregressive methods, namely Burg and Yule-Walker algorithms, have been applied to 31 P NMR free induction decays of packed human tumor cells where the signalto-noise ratio was limited by short duration records.
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