On a nonlinear prediction analysis for multi-dimensional stochastic processes with its applications to data analysis
type: Item
instance of: scholarly article
title: On a nonlinear prediction analysis for multi-dimensional stochastic processes with its applications to data analysis
zbMATH Open document ID: 0974.62086
author: Yasunori Okabe
author: Akihito Kaneko
published in: Hokkaido Mathematical Journal
publication date: 2001-12-13T00:00:00Z
review text: The authors are concerned here with the provision of (a) a weakening of existing conditions for the solution of the nonlinear prediction problem for stochastic processes (specifically the boundedness and the non-degenerate properties), and (b) computable algorithms for the calculation of the nonlinear predictor. Earlier results are extended to the case of multi-dimensional stochastic processes, this being effected by the development of a causal analysis for multi-dimensional data. The results are applied to data arising in various meteorological phenomena.
Mathematics Subject Classification ID: 62M20
Mathematics Subject Classification ID: 62P12
Mathematics Subject Classification ID: 60G25
Mathematics Subject Classification ID: 86A10
zbMATH DE Number: 1556320
zbMATH Keywords: nonlinear prediction analysis
zbMATH Keywords: nonlinear causal analysis
zbMATH Keywords: fluctuation-dissipation theorem
zbMATH Keywords: meteorological phenomena
reviewed by: Andrew Dale
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.14492/hokmj/1350912994
OpenAlex ID: W2028837117
DOI: 10.14492/HOKMJ/1350912994
description: scientific article; zbMATH DE number 1556320