Long-memory ARFIMA model for DNA sequences of influenza A virus

Abstract

Influenza viruses are divided into three types: A, B and C. Among them, type A virus is the most virulent human pathogen and causes the most severe disease. In this paper, we propose a new time series model for influenza A virus DNA sequence, i.e.chaos game representation (CGR) radians series. The CGR coordinates are converted into a time series model, and a long-memory ARFIMA( p,d,q ) model is introduced to simulate the time series model. We select randomly 10 H1N1 sequences and 10 H3N2 sequences in analysis. we find in these data a remarkably long-range correlation and fit the model reasonably by ARFIMA (p,d,q) model, and also find that we can use different ARFIMA models to identify the two kinds of sequences, i.e. ARFIMA(0, d ,5) model and ARFIMA(1, d ,1) model that can identify H1N1 and H3N2 respectively.