Predicting compositional time series via autoregressive Dirichlet estimation

• 来源期刊: 中国科学（信息科学）
• 年，卷（期）: 2018,（9）
• 页码范围: 268-270
• 页数: 3页
• 语种: 中文

摘要

In recent years,compositional time series (CTS) prediction has become a widely applied data analysis method for modeling tactile sequence data [1],hydrological time series data using a four-stage algorithm (denoising,decomposition,components prediction and ensemble) [2],and daily and monthly extreme temperature data [3,4].