Department of Mathematical Science,
Department of Computational Science
University of Texas at El Paso
Department of Data Science
Ramapo College of New Jersey
Mahwah, New Jersey
Multifractal Analysis of Daily US COVID-19 Cases
In this work, we applied the multifractal detrended fluctuation analysis (MFDA) to analyze the highly irregular behavior or volatility clustering of daily COVID-19 cases in the United States. We use the multifractal spectrum of the MFDFA to characterize the path and predict short or long-memory behavior of the time series on different time scales. Empirical results from the generalized Hurst exponent (gHE) and multifractal spectrum estimation indicates that path of the COVID-19 cases is multifractal and keeps becoming less fractal as the days progresses.