一种新的软剪裁离散Beta GARCH模型及其在麻疹感染中的应用

Pub Date : 2023-02-09 DOI:10.3390/stats6010018

Huaping Chen

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引用次数: 1

摘要

在本文中，我们开发了一种新的软剪裁离散βGARCH（ScDBGARCH）模型，该模型为具有欠分散、等分散或过分散的有界时间序列建模提供了一种可用的方法。新模型不仅允许正依赖，也允许负依赖。建立了模型的随机性质，并将这些结果用于分析新模型的条件最大似然（CML）估计器的渐近性质。此外，我们将新模型应用于麻疹感染，以显示其改进的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A New Soft-Clipping Discrete Beta GARCH Model and Its Application on Measles Infection

In this paper, we develop a novel soft-clipping discrete beta GARCH (ScDBGARCH) model that provides an available method to model bounded time series with under-dispersion, equi-dispersion or over-dispersion. The new model not only allows positive dependence, but also negative dependence. The stochastic properties of the models are established, and these results are, in turn, used in the analysis of the asymptotic properties of the conditional maximum likelihood (CML) estimator of the new model. In addition, we apply the new model to measles infection to show its improved performance.

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