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In probability and statistics, decoupling is a reduction of a sample statistic to an average of the statistic evaluated on several independent sequences of the random variable. This sum, conditioned on all but one of the independent sequences, becomes a sum of independent random variables. Decoupling is used in the study of U statistics, where decoupling should not be confused with Hoeffding's decomposition, however. [1] (Such "decoupling" is unrelated to the use of " couplings" in the study of stochastic processes.)
References
- ^ Victor H. de la Peña and Evariste Giné (1999). Decoupling: From Dependence to Independence. Springer Verlag. ISBN 978-0-387-98616-6.
 | This probability-related article is a stub. You can help Wikipedia by expanding it. |
| An editor has performed a search and found that
sufficient sources exist to establish the subject's
notability. (April 2021) |
In probability and statistics, decoupling is a reduction of a sample statistic to an average of the statistic evaluated on several independent sequences of the random variable. This sum, conditioned on all but one of the independent sequences, becomes a sum of independent random variables. Decoupling is used in the study of U statistics, where decoupling should not be confused with Hoeffding's decomposition, however. [1] (Such "decoupling" is unrelated to the use of " couplings" in the study of stochastic processes.)
References
- ^ Victor H. de la Peña and Evariste Giné (1999). Decoupling: From Dependence to Independence. Springer Verlag. ISBN 978-0-387-98616-6.
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| This probability-related article is a stub. You can help Wikipedia by expanding it. |