The theory of KM2O-Langevin equations and applications to data analysis (II): Causal analysis (1)

DOI10.1017/S0027763000004827zbMath0804.60054MaRDI QIDQ4305902

Yasunori Okabe, Akihiko Inoue

Publication date: 13 October 1994

Published in: Nagoya Mathematical Journal (Search for Journal in Brave)

zbMATH Keywords

random phenomena\(\text{KM}_ 2 \text{O}\)-Langevin equationcanonical representtion for stationary processesdefinition of causalityprediction problem for stationary time series

Mathematics Subject Classification ID

Stochastic analysis (60H99)

Related Items (7)

The theory of KM₂O-Langevin equations and its applications to data analysis (III): Deterministic analysis ⋮ A time series analysis of economical phenomena in Japan's lost decade (1): determinacy property of the velocity of money and equilibrium solution ⋮ Time series analysis and prediction on complex dynamical behavior observed in a blast furnace ⋮ On a nonlinear risk analysis for stock market indexes ⋮ Nonlinear time series analysis based upon the Fluctuation-Dissipation theorem ⋮ Detection of changes in non-linear dynamics for time series based on the theory of \(\mathrm{KM}_2 \mathrm O\)-Langevin equations ⋮ Time series analysis with wavelet coefficients

Cites Work

• The theory of KM\(_2\)O-Langevin equations and its applications to data analysis. I: Stationary analysis
• On a multi-dimensional \([\alpha,\beta,\gamma\)-Langevin equation]
• A generalized fluctuation-dissipation theorem for the one-dimensional diffusion process
• On the theory of Brownian motion with the Alder-Wainwright effect
• On the theory of discrete KMO-Langevin equations with reflection positivity. I
• Application of the theory of \(\text{KM}_ 2\)O-Langevin equations to the linear prediction problem for the multi-dimensional weakly stationary time series
• KMO-Langevin equation and fluctuation-dissipation theorem. I
• KMO-Langevin equation and fluctuation-dissipation theorem. II
• On the theory of discrete KMO-Langevin equations with reflection positivity. II
• On the theory of discrete KMO-Langevin equation with reflection positivity. III
• The Fitting of Time-Series Models
• On periodicity in series of related terms
• Investigating Causal Relations by Econometric Models and Cross-spectral Methods
• On the fitting of multivariate autoregressions, and the approximate canonical factorization of a spectral density matrix

This page was built for publication: The theory of KM₂O-Langevin equations and applications to data analysis (II): Causal analysis (1)