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Fitting nonstationary time series data: A two-step procedure versus the true state space model by Fei Gu (Colloquium)

Friday October 05, 2012
3:00pm - 4:30pm
Watson Library, 455
Fitting general state space models usually requires extensive programming skills. Using existing software packages, a two-step procedure is proposed and compared to the true state space model in a simulation study with nonstationary time series data. For the model considered in this study, the two-step procedure provided acceptable point estimates, while the standard errors are greatly inflated. In addition, it is showed that the two-step procedure is very easy to implement and extremely fast. Based on the results of the simulation study, it is concluded that the two-step procedure provides an easy access for researchers to obtain useful preliminary results in multivariate time series data analysis.
Contact: 785-864-3353, quant@ku.edu
Department: Center for Research Methods and Data Analysis
Ticket Cost: Free