论文标题
积极的时间序列回归模型
Positive Time Series Regression Models
论文作者
论文摘要
在本文中,我们讨论了时间序列的动态ARMA型回归模型,以$(0,\ infty)$为单位。在提议的模型中,条件平均值是由包含自回归和移动平均项,随时间变化的回归剂,未知参数和链接函数的动态结构建模的。我们介绍了新的模型类别,并讨论了部分最大似然估计,假设测试推断,诊断分析和预测。
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.