论文标题
Gartfima工艺及其基于经验光谱密度估计
GARTFIMA Process and its Empirical Spectral Density Based Estimation
论文作者
论文摘要
在本文中，我们介绍了Gegenbauer自动回归的钢化回火分数移动平均值（GARTFIMA）过程。我们为引入过程的频谱密度和自动助力函数工作。参数估计是使用经验光谱密度借助非线性最小二平方技术和晶体可能性估计技术进行的。在模拟数据上评估了提出的估计技术的性能。此外，与其他时间序列模型相比，引入的过程被证明可以更好地对现实世界数据进行建模。
In this article, we introduce a Gegenbauer autoregressive tempered fractionally integrated moving average (GARTFIMA) process. We work on the spectral density and autocovariance function for the introduced process. The parameter estimation is done using the empirical spectral density with the help of the nonlinear least square technique and the Whittle likelihood estimation technique. The performance of the proposed estimation techniques is assessed on simulated data. Further, the introduced process is shown to better model the real-world data in comparison to other time series models.
