比利时vs摩洛哥足彩
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university of california san diego
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math 288 - probability & statistics seminar
claudia kirch
karlsruhe institute of technology
evaluating stationarity via change-point alternatives with applications to fmri data
abstract:
functional magnetic resonance imaging (fmri) is now a well established technique for studying the brain. however, in many situations, such as when data are acquired in a resting state, it is difficult to know whether the data are truly stationary or if level shifts have occurred. to this end, change-point detection in sequences of functional data is examined where the functional observations are dependent and where the distributions of change-points from multiple subjects are required. of particular interest is the case where the change-point is an epidemic change -- a change occurs and then the observations return to baseline at a later time. the case where the covariance can be decomposed as a tensor product is considered with particular attention to the power analysis for detection. this is of interest in the application to fmri, where the estimation of a full covariance structure for the three-dimensional image is not computationally feasible. using the developed methods, a large study of resting state fmri data is conducted to determine whether the subjects undertaking the resting scan have non-stationarities present in their time courses. it is found that a sizeable proportion of the subjects studied are not stationary. the change-point distribution for those subjects is empirically determined, as well as its theoretical properties examined. this is joint work with john aston (warwick university).
dimitris politis
march 11, 2013
11:00 am
ap&m 7321
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