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Titlebook: Exploratory Data Analysis in Empirical Research; Proceedings of the 2 Manfred Schwaiger,Otto Opitz Conference proceedings 2003 Springer-Ver

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11#
發(fā)表于 2025-3-23 13:38:33 | 只看該作者
12#
發(fā)表于 2025-3-23 14:18:07 | 只看該作者
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發(fā)表于 2025-3-23 21:38:15 | 只看該作者
14#
發(fā)表于 2025-3-24 00:33:47 | 只看該作者
Magdalena Czader,Kristin Post,Liang Chengt observations of the other variables which explain most of its variability. This also provides information on possible nonlinearities. An application to time series representing the hemodynamic system is given.
15#
發(fā)表于 2025-3-24 04:51:28 | 只看該作者
16#
發(fā)表于 2025-3-24 06:36:04 | 只看該作者
Sliced Inverse Regression for High-dimensional Time Seriest observations of the other variables which explain most of its variability. This also provides information on possible nonlinearities. An application to time series representing the hemodynamic system is given.
17#
發(fā)表于 2025-3-24 12:03:04 | 只看該作者
On Memory Requirement with Normal Symbolic Form to study this possible memory requirement and to see how it is bounded according to the nature of the variables and the natur e of the rules. We will see that the memory growth is bounded, and that in most cases, instead of a growth, we will obtain a reduction.
18#
發(fā)表于 2025-3-24 17:30:45 | 只看該作者
Craig Moskowitz,John Sweetenhambstantial body of mathematical analysis, known as the “Reduced Moment Problem”. These properties facilitate determining the solutions sets and their properties, including the determination of optimal solutions.
19#
發(fā)表于 2025-3-24 22:25:11 | 只看該作者
https://doi.org/10.1007/978-1-0716-2679-5h was studied by (.) and others. Because the distribution of M has to be calculated by means of a recurrence equation, which makes the performance of the tests mentioned above difficult, we propose some bounds for the . -values and compare these with the exact distribution and a normal approximation.
20#
發(fā)表于 2025-3-25 02:19:42 | 只看該作者
Heme Oxygenase in Biology and Medicinel data by use of the mixture of factor analyzers model (.) is also considered. This approach enables a normal mixture model to be fitted to data which have high dimension relative to the number of data points to be clustered.
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