MODELING NONLINEAR TIME SERIES USING IMPROVED LEAST SQUARES METHOD
From MaRDI portal
Publication:5484872
DOI10.1142/S0218127406014927zbMath1116.37317OpenAlexW2038238162MaRDI QIDQ5484872
Tomomichi Nakamura, Michael Small
Publication date: 21 August 2006
Published in: International Journal of Bifurcation and Chaos (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1142/s0218127406014927
model selectionleast squares methodover-Fittingdescription lengthnonlinear time series modelingmodel degeneracy
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Time series analysis of dynamical systems (37M10)
Related Items (3)
Nonlinear dynamical system identification with dynamic noise and observational noise ⋮ The use of synthetic input sequences in time series modeling ⋮ A COMPARATIVE STUDY OF INFORMATION CRITERIA FOR MODEL SELECTION
Cites Work
- Unnamed Item
- A two-dimensional mapping with a strange attractor
- Estimating the dimension of a model
- Parametric, nonparametric and parametric modelling of a chaotic circuit time series
- On selecting models for nonlinear time series
- Embedding as a modeling problem
- Comparisons of new nonlinear modeling techniques with applications to infant respiration.
- The double scroll
- Noise Reduction of Chaotic Systems by Kalman Filtering and by Shadowing
- MDL denoising
- A COMPARATIVE STUDY OF MODEL SELECTION METHODS FOR NONLINEAR TIME SERIES
- REFINEMENTS TO MODEL SELECTION FOR NONLINEAR TIME SERIES
- Structure-selection techniques applied to continuous-time nonlinear models
- A new look at the statistical model identification
This page was built for publication: MODELING NONLINEAR TIME SERIES USING IMPROVED LEAST SQUARES METHOD