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Can I read A Forecasting Procedure for Nonlinear Autoregressive Time Series Models on EtoBox?
A Forecasting Procedure for Nonlinear Autoregressive Time Series Models by Yuzhi Cai is a Economics, Econometrics and Finance article available to read on EtoBox.
What is A Forecasting Procedure for Nonlinear Autoregressive Time Series Models about?
## Abstract Forecasting for nonlinear time series is an important topic in time series analysis. Existing numerical algorithms for multi‐step‐ahead forecasting ignore accuracy checking, alternative Monte Carlo methods are also computationally very demanding and their accuracy is difficult to control too. In this paper a numerical forecasting procedure for nonlinear autoregressive time series models is proposed. The forecasting procedure can be used to obtain approximate __m__‐step‐ahead predictive probability density functions, predictive distribution functions, predictive mean and variance, etc. for a range of nonlinear autoregressive time series models. Examples in the paper show that the forecasting procedure works very well both in terms of the accuracy of the results and in the ability to deal with different nonlinear autoregressive time series models. Copyright © 2005 John Wiley & Sons, Ltd.
Who reads A Forecasting Procedure for Nonlinear Autoregressive Time Series Models?
It is typically read by researchers, students, and practitioners in Economics, Econometrics and Finance.
- Author
- Yuzhi Cai
- Publisher
- John Wiley and Sons; Wiley (John Wiley & Sons); John Wiley & Sons Inc.; Wiley (ISSN 0277-6693)
- Published
- 2005
- Language
- EN
- Field
- Economics, Econometrics and Finance (Social Sciences)