True 3-D displays for avionics and mission crewstations
Elizabeth A. Sholler, Frederick M. Meyer, et al.
SPIE AeroSense 1997
We consider the problem of estimating the order of a stationary ergodic Markov chain. Our focus is on estimators which satisfy a generalized Neyman-Pearson criterion of optimality. Specifically, the optimal estimator minimizes the probability of underestimation among all estimators with probability of overestimation not exceeding a given value. Our main result identifies the best exponent of asymptotically exponential decay of the probability of underestimation. We further construct a consistent estimator, based on Kullback-Leibler divergences, which achieves the best exponent. We also present a consistent estimator involving a recursively computable statistic based on appropriate mixture distributions; this estimator also achieves the best exponent for underestimation probability. © 1996 IEEE.
Elizabeth A. Sholler, Frederick M. Meyer, et al.
SPIE AeroSense 1997
Michael C. McCord, Violetta Cavalli-Sforza
ACL 2007
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CoNEXT 2006
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