A seasonal periodic long memory model for monthly river flows

被引:32
作者
Ooms, M [1 ]
Franses, PH [1 ]
机构
[1] Erasmus Univ, Inst Econometr, NL-3000 DR Rotterdam, Netherlands
关键词
seasonal difference; periodic model; long memory; PARFIMA; SPARFIMA;
D O I
10.1016/S1364-8152(01)00025-1
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Based on simple time series plots and periodic sample autocorrelations, we document that monthly river flow data displays long memory, in addition to pronounced seasonality. In fact, it appears that the long memory characteristics vary with the season. To describe these two properties jointly, we propose a seasonal periodic long memory model and fit it to the well-known Fraser river data (to be obtained from Statlib at http://iib.stat.cm.edu/datasets/). We provide a statistical analysis and provide impulse response functions to show that shocks in certain months of the year have a longer lasting impact than those in other months. (C) 2001 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:559 / 569
页数:11
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