Abstract
Most of the recent work in time series analysis has been done on the assumption
that the structure of the series can be described by linear time series models. However, there
are occasions when subject-matter, theory or data suggest that linear models are
unsatisfactory. In those cases it is desirable to look at non-linear alternatives. This paper
gives an overview of the most recent developments in this area. Particular attention is paid to
the strengths and weaknesses (advantages and disadvantages) of a large number of
models and tests for non-linearity, focusing on 'ready-to-use'issues rather than discussing
technical details. Various problems in forecasting from non-linear models are discussed.
Some guidelines for practical non-linear time series modelling and forecasting are also
included.
that the structure of the series can be described by linear time series models. However, there
are occasions when subject-matter, theory or data suggest that linear models are
unsatisfactory. In those cases it is desirable to look at non-linear alternatives. This paper
gives an overview of the most recent developments in this area. Particular attention is paid to
the strengths and weaknesses (advantages and disadvantages) of a large number of
models and tests for non-linearity, focusing on 'ready-to-use'issues rather than discussing
technical details. Various problems in forecasting from non-linear models are discussed.
Some guidelines for practical non-linear time series modelling and forecasting are also
included.
| Original language | English |
|---|---|
| Pages (from-to) | 135-156 |
| Number of pages | 21 |
| Journal | International Journal of Forecasting |
| Volume | 8 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1992 |
| Externally published | Yes |