Biostatics Seminar Series with Maryclare Griffin
January 24, 2020
10:00 am-11:00 am
Life Science Laboratories
Room: LSL S330
UMass Amherst Campus
The Department of Biostatistics and Epidemiology, part of the School of Public Health and Health Sciences, will host a seminar, as part of the Biostatistics program: “Estimation for Possibly Non-Stationary Long Memory Processes."
Time series data is increasingly prevalent, however common time series models can fail to capture the complex dynamics of time series data in practice. In this talk, we focus on a specific model - the ARFIMA(p, d, q) model - and the assumption of stationarity. Assuming that a process is stationary is technically convenient, but may not be appropriate in practice. In this paper, we introduce a likelihood-based approach to estimating the parameters of the popular ARFIMA(p, d, q) model without assuming stationarity. This allows us to obtain better estimates of the differencing parameter d and implement likelihood-based tests of stationarity.