Normal residual is one of the usual assumptions of autoregressive models but in practice sometimes we are faced with non-negative residuals case. In this paper we consider some autoregressive models with non-negative residuals as competing models and we have derived the maximum likelihood estimators of parameters based on the modified approach and EM algorithm for the competing models. Also,...

this article is a comparative study of estimation power of artificial neural networks and autoregressive time series models in inflation forecasting. using 37 years iran’s inflation data, neural networks performs better on average for short horizons than autoregressive models. this study shows usefulness of early stopping technique in learning stage of neural networks for estimating time series...

Functional autoregressive models are popular for functional time series analysis, but the standard formulation fails to address seasonal behaviour in data. To overcome this shortcoming, we introduce models. For model of order one, derive sufficient stationarity conditions and limiting behaviour, provide estimation prediction methods. Moreover, consider a portmanteau test testing adequacy model,...