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Titlebook: COMPSTAT; Proceedings in Compu Jelke G. Bethlehem,Peter G. M. Heijden Conference proceedings 2000 Springer-Verlag Berlin Heidelberg 2000 Bo

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51#
發(fā)表于 2025-3-30 10:12:00 | 只看該作者
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發(fā)表于 2025-3-30 12:58:18 | 只看該作者
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發(fā)表于 2025-3-30 16:33:21 | 只看該作者
https://doi.org/10.1007/978-3-642-57678-2Bootstrapping; Computational Statistics; Computergesteuerte Statistik; Factor analysis; Internet; Likelih
54#
發(fā)表于 2025-3-30 22:18:41 | 只看該作者
978-3-7908-1326-5Springer-Verlag Berlin Heidelberg 2000
55#
發(fā)表于 2025-3-31 03:27:22 | 只看該作者
56#
發(fā)表于 2025-3-31 06:40:31 | 只看該作者
Official Statistics: an estimation strategy for the IT-erad towards full numerical consistency of its statistical estimates, given a matched data file containing all available register and survey data about the target population. The key element of the estimation procedure is repeated re-calibration of survey data sets, i.e. a new set of raising weights is
57#
發(fā)表于 2025-3-31 10:47:29 | 只看該作者
58#
發(fā)表于 2025-3-31 15:35:10 | 只看該作者
Spatio-temporal hierarchical modeling of an infectious disease from (simulated) count data mechanism directly requires data that would amount to observing (imperfectly) all individuals’ disease statuses along their space-time lines in the region and time period of interest. More likely, data consist of spatio-temporal aggregations that give small-area counts of the number infected during
59#
發(fā)表于 2025-3-31 19:11:06 | 只看該作者
GBMs: GLMs with bilinear terms combined: exploratory analysis and explicit modeling. It turns out that the wide diversity of correlative methods can be considered as minor variations of a single model which is introduced in the standard framework set for generalized linear models. The paper presents this unifying approach and il
60#
發(fā)表于 2025-3-31 23:28:55 | 只看該作者
Generalized calibration and application to weighting for non-responsecase. The dissymmetry of the variables receives a very interesting application when we apply generalised calibration to the problem of weighting for non-response: one set of variables is connected to factors inducing nonresponse, the second one to variables correlated to the variable of interest. A
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