Summary
Robust multivariate prediction and interpolation problems for statistically contaminated vector valued second order stationary processes are considered. The statistical contamination is modeled by requiring that the spectral density matrices of the processes lie within certain nonparametric classes. Both prediction and interpolation are then formalized as games whose saddle point solutions are sought. Finally, such solutions are found and analyzed, for two specific multivariate spectral classes.
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Research supported by the Air Force Office of Scientific Research under Grants AFOSR-83-0229 and AFOSR-82-0030
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Tsaknakis, H., Kazakos, D. & Papantoni-Kazakos, P. Robust prediction and interpolation for vector stationary processes. Probab. Th. Rel. Fields 72, 589–602 (1986). https://doi.org/10.1007/BF00344722
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DOI: https://doi.org/10.1007/BF00344722