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.
翻译:在本文中,我们讨论ARMA型动态回归模型,用于以(0)/(infty)美元计算的时间序列值。在拟议模型中,有条件平均值以动态结构为模型,包含自动递减和移动平均条件、时间递减递减器、未知参数和链接功能。我们引入了新的模型类别,并讨论部分最大可能性估算、假设测试推论、诊断分析和预测。