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A Sequential Multi-Hypothesis Test for the Mean Function of a Discrete-Time Gaussian Process |
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| Abstract: | Abstract A sequential multi-hypothesis test for the mean function of a discrete-time Gaussian process with known covariance kernel is developed. It is obtained by applying the Bechhofer-Kiefer-Sobel generalized sequential probability ratio test GSPRT, and its properties are studied analytically. Selected applications to i.i.d. normal random variables, observation in a time series AR(1) model, and Wiener processes are given. |
| Keywords: | Bechhofer-Kiefer-Sobel GSPRT Gaussian processes Mean functions Multi-hypothesis testing Multivariate normal distribution |