This paper presents a general method to fit the Schöner-Haken-Kelso (SHK) model of human movement phase transitions directly to time series data. A robust variant of the extended Kalman filter technique is applied to the data of a single subject The options of covariance resetting and iteration within recursion were used to obtain time-dependent estimates of both the α and β parameters in the SHK model. Comparison between transition onset time and the time at which |β(t | T)/α(t | T)| becomes critical indicates that the transitions are advanced by noise. The method can be extended to handle non-normal data and generalization across subjects and/or experimental conditions.
|Original language||English (US)|
|Number of pages||16|
|Journal||British Journal of Mathematical and Statistical Psychology|
|State||Published - Nov 1 2003|
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Arts and Humanities (miscellaneous)