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A simple on-line procedure is considered for the prediction of a real valued sequence. The algorithm is based on a combination of several simple predictors. If the sequence is a realization of an unbounded stationary and ergodic random process then the average of squared errors converges, almost surely, to that of the optimum, given by the Bayes predictor.(More)
Estimation of conditional distributions is considered. It is assumed that the conditional distribution is either discrete or that it has a density with respect to the Lebesgue-Borel-measure. Partitioning estimates of the conditional distribution are constructed and results concerning consistency and rate of convergence of the integrated total variation(More)
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