摘要
基于CGR-游走模型和分数阶差分,运用时间序列模型分析甲型流感病毒。基于详细HP模型,先将甲流病毒H5N1的蛋白质序列转化成CGR时间序列,再引入长记忆ARFIMA(p,d,q)模型拟合此类序列。发现随机得到的9条H5N1的蛋白质序列都具有长相关性且拟合良好,还发现这类序列都可以用ARFIMA(1,d,1)模型加以识别。
Based on the chaos game representation walk model and the integer-order difference, this paper presents the time series model to study the influenza A virus. Based on the detailed HP model, H5N1 protein sequences are converted into the CGR time series , and the long memory ARFIMA（p,d,q） model is introduced to simulate this kind of sequences. The 9 H5N1 sequences are selected randomly to analysis. It is found that the.se sequences have remarkably long-rang correlations and fit reasonably and also uncover that ARFIMA（ 1 ,d, 1 ） models are used to identify the sequences.
出处
《江南大学学报（自然科学版）》
CAS
2012年第6期727-730,共4页
Joural of Jiangnan University (Natural Science Edition)
基金
国家自然科学基金项目(11271163)
