Positive Time Series Regression Models

Abstract

In this paper we discuss dynamic ARMA-type regression models for time series taking values in $(0,\infty )$. In the proposed model, the conditional mean is modeled by a dynamic structure containing autoregressive and moving average terms, time-varying regressors, unknown parameters and link functions. We introduce the new class of models and discuss partial maximum likelihood estimation, hypothesis testing inference, diagnostic analysis and forecasting.