Investigating asymptotic properties of vector nonlinear time series models

DOI10.1016/J.CAM.2011.07.018zbMath1231.62158OpenAlexW2145687240MaRDI QIDQ645738

Ioana Banicescu, Jane L. Harvill, John Patrick Lestrade, Ricolindo L. Cariño

Publication date: 10 November 2011

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2011.07.018

zbMATH Keywords

dynamic loop schedulingvector FCAR models

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Parallel numerical computation (65Y05)

Related Items (1)

Hybrid regression model for near real-time urban water demand forecasting

Uses Software

• R
• Snow
• snow

Cites Work

• Unnamed Item
• Functional coefficient autoregressive models for vector time series
• Addressing the stochastic nature of scientific computations via dynamic loop scheduling
• Nonlinear time series. Nonparametric and parametric methods
• Functional Coefficient Autoregressive Models: Estimation and Tests of Hypotheses
• Functional-Coefficient Regression Models for Nonlinear Time Series
• Adaptive Varying-Coefficient Linear Models
• Functional-Coefficient Autoregressive Models
• Miscellanea. A note on tests for nonlinearity in a vector time series

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