期刊
ENVIRONMETRICS
卷 15, 期 4, 页码 313-335出版社
WILEY
DOI: 10.1002/env.642
关键词
trend assessment; long memory dependence; fractionally differenced process; discrete wavelet transform; time series analysis
In this article we consider trend to be smooth deterministic changes over long scales, and tackle the problem of trend estimation in the presence of long memory errors (slowly decaying autocorrelations). Using the fractionally differenced (FD) process as a motivating example of such a long memory process, we demonstrate how the discrete wavelet transform (DWT) is a natural choice at extracting a polynomial trend from such an error process. We investigate the statistical properties of the trend estimate obtained from the DWT, and provide pointwise and simultaneous confidence intervals for the estimate. Based on evaluating the power in the trend estimate relative to the estimated errors, we provide a test of nonzero trend. We finish by applying the methods to a climatological example. Copyright (C) 2004 John Wiley Sons, Ltd.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据