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搜索结果: 1-15 共查到Bayesian model相关记录17条 . 查询时间(0.14 秒)
This paper presents a model-based monitoring framework for the detection of fatigue-related crack damages in plate-type structures commonly seen in aluminum ship hulls. The monitoring framework involv...
We then show how to enrich the apparatus to handle pragmatic reasoning about the values of free variables, explore its predictions about the interpretation of scalar adjectives, and show how this mo...
Bayesian model averaging (BMA) is a statistical method for post-processing forecast ensembles of atmospheric variables, obtained from multiple runs of numerical weather prediction models, in order to ...
Modern phrase-based machine translation systems make extensive use of wordbased translation models for inducing alignments from parallel corpora. This is problematic, as the systems are incapable of a...
The joint modeling of longitudinal and time-to-event data is an active area of statistics research that has received a lot of attention in the recent years. More recently, a new and attractive applica...
In objective Bayesian model selection, no single criterion has emerged as dominant in defining objective prior distributions. Indeed, many criteria have been separately proposed and utilized to propos...
In objective Bayesian model selection, no single criterion has emerged as dominant in defining objective prior distributions. Indeed, many criteria have been separately proposed and utilized to propos...
Bayesian methods - either based on Bayes Factors or BIC - are now widely used for model selection. One property that might reasonably be demanded of any model selection method is that if a modelM1 is...
We develop a fully Bayesian, computationally efficient framework for incorporating model uncertainty into Type II Tobit models and apply this to the investigation of the determinants of Foreign Direct...
We present a simple mathematical criterion for determining whether a given statistical model does not describe several independent sets of measurements, or data modes, adequately. We derive this crite...
Nuclear Magnetic Resonance (NMR) spectra are widely used in metabolomics to obtain profiles of metabolites dissolved in biofluids such as cell supernatants. Methods for estimating metabolite concent...
One of the most popular copulas for modeling dependence structures is t-copula.Recently the grouped t-copula was generalized to allow each group to have one mem-ber only,so that a priori grouping is n...
Implementing Bayesian variable selection for linear Gaussian regression models for analysing high dimensional data sets is of current interest in many fields. In order to make such analysis operation...
In this article I develop a simple and eective device for ascertaining the quality of the modeling choices and detecting lack-of-fit. I specify an articial autoregres- sive structure (AAR) in the pr...
Suppose that S(Y) is a function of data Y and a model parameter, and suppose that the sampling distribution of S(Y) is invariant when evaluated at , the true (i.e., data-generating) value of. Then S...

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