摘要
介绍应用小波分析理论解决时间序列统计数据的测量误差消除问题,实例证明借助离散小波分解与重构手段,可有效地从误差干扰的统计数据序列中提取统计数据的原始特征.完成CPI经济序列数据预测,为CPI统计数据的误差消除引入一种有效方法.
This paper introduces the application of wavelet analysis theory to eliminate time sequence statistics data measurement error problems. Practical studies prove that discretion wavelet decomposition and reconstruction method can effectively extract statistics data of the original features from error interference statistical data sequence. Consequently, we complete CPI economic series data prediction and introduce an effective method for eliminating the error CPI statistics data.
出处
《数学的实践与认识》
CSCD
北大核心
2014年第8期159-163,共5页
Mathematics in Practice and Theory
基金
2012年度山东省统计局科研课题"基于ANFS模型的经济数据预测研究"(KT12058)
