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Titlebook: COMPSTAT 1984; Proceedings in Compu T. Havránek,Z. ?idák,M. Novák Conference proceedings 1984 Springer-Verlag Berlin Heidelberg 1984 effici

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樓主: 粗野的整個
31#
發(fā)表于 2025-3-26 23:53:16 | 只看該作者
32#
發(fā)表于 2025-3-27 03:37:31 | 只看該作者
33#
發(fā)表于 2025-3-27 07:50:25 | 只看該作者
34#
發(fā)表于 2025-3-27 10:20:29 | 只看該作者
Hierarchical Inferencegorithm, with constraints of validity, is used to induce the final hierarchy..An application to pattern recognition is proposed, which has permitted to induce some aggregation indices adapted to particular two-dimensionnal repartition of points.
35#
發(fā)表于 2025-3-27 15:25:14 | 只看該作者
J. David Allan,Marí M. Castillo discussed, and several alternative approaches are shown to be equivalent. The modified Kalman filter is then used to compute the likelihood. Computational savings arising from the special structure of the Kalman filter conditional covariance matrices are discussed, and different state space representations are compared.
36#
發(fā)表于 2025-3-27 18:11:01 | 只看該作者
https://doi.org/10.1007/978-1-4020-5583-6imates. The main aim of these simulations (results given in §4) is the comparison of these estimates from the point of view of their robustness against contaminations relative to the law of ε = Y-r(X) assumed independent on X and Y and the regression function assumed to be a polynomial.
37#
發(fā)表于 2025-3-28 00:39:11 | 只看該作者
38#
發(fā)表于 2025-3-28 06:05:59 | 只看該作者
39#
發(fā)表于 2025-3-28 08:04:07 | 只看該作者
40#
發(fā)表于 2025-3-28 13:17:07 | 只看該作者
Robustness in Parametric and Non-Parametric Regression Estimation: An Investigation by Computer Simuimates. The main aim of these simulations (results given in §4) is the comparison of these estimates from the point of view of their robustness against contaminations relative to the law of ε = Y-r(X) assumed independent on X and Y and the regression function assumed to be a polynomial.
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