Research and Simulation of Network Self-Similar Traffic Flow Model Based on FARIMA with Three Core Functions

The study and simulation of network self-similar traffic flow based on FARIMA methodology includes three MATLAB functions: av.m (for computing mean values), far.m (for calculating fractional moving averages), and zsrs.m (for determining standardized residuals). Detailed implementation approaches and algorithmic explanations are available in the associated paper and model documentation.

Generating FARIMA Time Series Using the Definition Method

Generating FARIMA time series via definition method and estimating HURST parameters to produce time series with long-range dependence characteristics, with implementation insights on fractional differencing and parameter estimation algorithms.