model selection 就是说 model有很多参数,参数空间组成了很多不同的model,model selection就是选择一个最合适的paramerter。 model averaging 就是说不知道拿个parameter 好,于是就用 avg的parameter 来做最后的model
A. (2011). Model selection and model averaging in behavioural ecology: The utility of the IT-AIC framework. Behavioral Ecology and Sociobiology, 65, 77-89.Richards SA, Whittingham MJ, Stephens PA (2010) Model selection and model averaging in behavioural ecology: the utility of the IT-AIC ...
Model averagingModel selectionSemiparametric partially linear modelWe study model selection and model averaging in semiparametric partially linear models with missing responses. An imputation method is used to estimate the linear regression coefficients and the nonparametric function. We show that the ...
used criteria, namely, Akaike information criterion, Bayesian information criterion and an adjustable prediction error sum of squares (APRESS) are investigated and their performance in model selection and model averaging is evaluated via a number of case studies using both simu- lation and real data....
Zucchini, "Post-model selection inference and model averaging," Pakistan Journal of Statistics and Operation Research, vol. 7, no. 2, pp. 347-361, 2011.Nguefack-Tsague, G. and Zucchini, W. Post-model selection inference and model averaging, Pakistan Journal of Statistics and Operation ...
Model selection, updating, and averaging for probabilistic fatigue damage prognosis This paper presents a method for fatigue damage propagation model selection, updating, and averaging using reversible jump Markov chain Monte Carlo simulat... X Guan,R Jha,Y Liu - 《Structural Safety》 被引量: 83发...
Meta-Analysis,Model Selection,Model Averaging Full-TextCite this paperAdd to My Lib Abstract: 模型选择与模型平均一直是统计学与计量经济学界研究的重要问题,本文依托Meta分析理论和方法,以分析豆科植物-根瘤菌互利共生合作系统的影响因素为例,比较模型选择与模型平均方法在Meta分析中的应用效果,结果表明模型平均方法...
Model Averaging and Stacking 本书的大多情况都是通过最小化平方和(回归),或最小化交叉熵(分类)来拟合。实际上,这两种方式都是最大化似然函数的实例。本章中我们介绍这种最大似然函数的方法——贝叶斯推理。我们还会探讨上章讲的自助法和贝叶斯的关系。最后,我们介绍一些模型平均和改善的技巧,包括committee methods...
我院在读博士生彭镜夫在《Journal of Econometrics》发表论文。该研究主要在嵌套模型框架下,对模型平均和模型选择的最优风险进行比较,从而说明模型平均方法在回归函数估计上相较于模型选择的优势。 论文题目 On improvability of model selection by model averaging ...
Model Selection中,Frequentist试图找到一个Model,它避免overfitting的方法是用Validation set;而Bayesian则对in consideration的所有Models做weighted averaging,所用weights就是各个Model的posterior p(Mi|D),因此对于Bayesian来说,应该叫Model Averaging或Model Comparison而不是Model Selection。奇妙的是,这种weighted averaging...