CMStatistics 2022: Start Registration
View Submission - CMStatistics
Title: Tempered fractionally integrated process with stable noise as a transient anomalous diffusion model Authors:  Krzysztof Burnecki - Wroclaw University of Science and Technology (Poland) [presenting]
Farzad Sabzikar - Iowa State University (United States)
Jinu Kabala - Iowa State University (United States)
Abstract: The autoregressive tempered fractionally integrated moving average (ARTFIMA) process is presented, which is obtained by taking the tempered fractional difference operator of the non-Gaussian stable noise. The tempering parameter makes the ARTFIMA process stationary for a wider range of the memory parameter values than for the classical autoregressive fractionally integrated moving average, and leads to semi-long range dependence and transient anomalous behavior. We investigate ARTFIMA dependence structure with stable noise and construct Whittle estimators. Finally, we illustrate the usefulness of the ARTFIMA process on a trajectory from a single-particle tracking experiment.