ON THE GEOMETRIC ERGODICITY OF THE MIXTURE AUTOREGRESSIVE MODEL

M. I. AKINYEMI, G. N. BOSHNAKOV

Abstract


Geometric ergodicity is very useful in establishing mixing conditions and central limit results for parameter estimates of a model. It also justifies the use of laws of large numbers and forms part of the basis for exploring the asymptotic theory of a model.
The class of mixture autoregressive (MAR) models provides a flexible way to model various features of time series data and is well suited for density forecasting. The MAR models are able to capture many stylised properties of real data, such as multimodality, asymmetry and heterogeneity. We show here that the MAR model is geometrically ergodic and by implication satisfies the absolutely regular and strong mixing conditions.

Full Text:

 Subscribers Only

Refbacks

  • There are currently no refbacks.


Copyright (c) 2017 Journal of the Nigerian Mathematical Society

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.