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標(biāo)題: Titlebook: On Model Uncertainty and its Statistical Implications; Proceedings of a Wor Theo K. Dijkstra Conference proceedings 1988 Springer-Verlag Be [打印本頁(yè)]

作者: Cession    時(shí)間: 2025-3-21 16:27
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作者: 敲詐    時(shí)間: 2025-3-21 22:29
Conference proceedings 1988 experiments are discussed. The emphasis is on the statistical implications for model assessment when the assessment is done with the same data that generated the model. This is a problem of long standing, notorious for its difficulty. Some contributors discuss this problem in an illuminating way. O
作者: Lineage    時(shí)間: 2025-3-22 00:58
Data-Driven Selection of Regressors and the Bootstrap,he usual unbiased estimate of the residual variance obtained by fitting all columns; and a is a positive number, often 2 but α = 1 or α = log n have also surfaced in the literature. The value of (1) is calculated for those sets of columns one is willing to consider and that model is chosen for which the criterion is minimal.
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作者: 原告    時(shí)間: 2025-3-22 11:42
Conference proceedings 1988thers, and this is a truly novel feature, investigate systematically whether sample re-use methods like the bootstrap can be used to assess the quality of estimators or predictors in a reliable way given the initial model uncertainty. The book should prove to be valuable for advanced practitioners and statistical methodologists alike.
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Model Selection in Multinomial Experiments,he . p, with p. = n./N, and the . prop(n.,...,n.). Another way of expressing this is that for each N we have defined a random vector .., taking values in .., the unit simplex in ... We use the convention of underlining random variables in this paper. Thus .. is a sequence of random vectors.
作者: correspondent    時(shí)間: 2025-3-23 13:36
On the Impact of Variable Selection in Fitting Regression Equations,tting the equation, dropping insignificant variables, and refitting. As is well known, this can seriously distort the conventional goodness-of-fit statistics. Furthermore, the bootstrap and jackknife may not help in high-dimensional cases.
作者: incisive    時(shí)間: 2025-3-23 17:34
Data-Driven Selection of Regressors and the Bootstrap,Suppose it is believed that some of the columns of X may be redundant, but it is not known which. Given the data a model search is carried out using the following criterion:.Here RSS(.) designates the residual-sum-of-squares obtained by regression on the p X-columns indexed by i., i.,...,i.; s. is t
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作者: depreciate    時(shí)間: 2025-3-24 09:15
Pitfalls for Forecasters,ecasts of macro-economic quantities. Two important problems may then occur, namely overfitting and datamining, which have been considered separately in literature, but the very close relationship between the two does not seem to have been discussed. Trying to avoid overfitting researchers often dele
作者: 值得尊敬    時(shí)間: 2025-3-24 14:12

作者: 可卡    時(shí)間: 2025-3-24 17:55
978-3-540-19367-8Springer-Verlag Berlin Heidelberg 1988
作者: Mobile    時(shí)間: 2025-3-24 20:08
On Model Uncertainty and its Statistical Implications978-3-642-61564-1Series ISSN 0075-8442 Series E-ISSN 2196-9957
作者: artless    時(shí)間: 2025-3-25 02:44

作者: 旁觀者    時(shí)間: 2025-3-25 03:28
On Cross-Validation for Predictor Evaluation in Time Series,s are proposed for prediction of squared prediction errors, and also for choosing among several predictor families. These procedures are compared in a simulation study. The conventional procedure appears to perform at least as well as the cross-validatory procedures.
作者: 手銬    時(shí)間: 2025-3-25 08:33
Lecture Notes in Economics and Mathematical Systemshttp://image.papertrans.cn/o/image/701031.jpg
作者: 我怕被刺穿    時(shí)間: 2025-3-25 11:53
https://doi.org/10.1007/978-3-642-61564-1Estimator; Factor analysis; Fitting; Time series; Variance; best fit; calculus; correlation; statistical met
作者: Brain-Imaging    時(shí)間: 2025-3-25 18:42
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