Hierarchical Bayesian
A Comparison of Hierarchical Bayesian Models for Small Area Estimation of Counts
... estimator. Hierarchical Bayesian approach to SAE problems offers several advantages over traditional SAE models including the ability of appropriately accounting for the type of surveyed ...
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Hierarchical Bayesian level set inversion
... fully Bayesian level set framework for the solution of the aforemen- tioned type of inverse problems has been recently de- veloped in ...proposed hierarchical Bayesian framework enables us to ...
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A Hierarchical Bayesian Model for Unsupervised Induction of Script Knowledge
... present a system which learns narrative chains from newswire texts. Relevant phrases are iden- tified based on shared protagonists. The phrases are clustered into equivalence classes and tempo- rally ordered using a ...
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Bayesian and hierarchical Bayesian analysis of response time data with concomitant variables
... the Bayesian framework. The present paper presents the Bayesian and hierarchical Bayesian analysis of re- sponse-time data in more general situations of more ...
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A hierarchical Bayesian approach for parameter estimation in HIV models
... The paper is organized as follows. In section 2, a hierarchical Bayesian approach is adopted to estimate the dynamic system parameters for the model (1.1), with the imple- mentation carried out using MCMC ...
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Hierarchical Bayesian level set inversion
... using hierarchical Bayesian methods in which these parameters are learned from the ...a hierarchical Bayesian level set method with a single scalar hierarchical parameter which deals ...
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Hierarchical Bayesian Estimation of System Parameters from Dynamic Responses
... the hierarchical Bayesian model based on dynamic responses, the unknown parameters of the system are assumed to obey the Gaussian normal distribution ~ N u , , and the error function vector is ...
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Hierarchical Bayesian Domain Adaptation
... We call our model hierarchical Bayesian domain adaptation, because it makes use of a hierarchical Bayesian prior. As an example, take the case of building a logistic classifier to decide if a ...
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Estimating breeding bird survey trends and annual indices for Canada: how do the new hierarchical Bayesian estimates differ from previous estimates?
... Figure A4.2. The proportion of species with BBS trend estimates that fall into the same “Status of Birds in Canada” (Environment Canada 2011) population status category (upper plot) or within 1 population status category ...
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An Infinite Hierarchical Bayesian Model of Phrasal Translation
... We have presented a novel method for learn- ing a phrase-based model of translation directly from parallel data which we have framed as learn- ing an inverse transduction grammar (ITG) us- ing a recursive Bayesian ...
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An Improved Hierarchical Bayesian Model of Language for Document Classification
... a hierarchical sampling model to eclipse that of the SVM because of the nature of the decision boundary, provided certain conditions are met: the SVM estimates a linear decision boundary, and the multinomial ...
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A Hierarchical Bayesian Language Model Based On Pitman Yor Processes
... mized over along with the discount parameters using cross-validation. Seating arrangements are Gibbs sampled as in Section 5 with the parame- ter values fixed. We find that HPYCV performs better than MKN (except ...
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Hierarchical Bayesian application to instantaneous rates tag-return models
... There has been a long debate on the application of Bayesian methods (for re- cent debate see (12; 27)). One of the most frequent complaints about Bayesian statistical methodology it is computationally ...
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Hierarchical Bayesian models for linear and non-linear animal growth curves.
... simple hierarchical analysis with two stages carried out one after the other (we first estimate the intercepts and slopes for each individual separately and then analyse these as if they were raw ...Our ...
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Hierarchical Bayesian inference for ion channel screening dose response data
... of Bayesian statistical models: one where all data points are treated equally (as though they were obtained from the same experiment); and another where we believe that each repeat of an experiment has distinct ...
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Hierarchical Bayesian Language Modelling for the Linguistically Informed
... So the base distribution for the prior of the word n-gram distribution Hu is the product of a distri- bution Gu over compound heads, given the same context u, and another n′-gram languag[r] ...
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Spatial Modeling and Mapping of Tuberculosis Using Bayesian Hierarchical Approaches
... a hierarchical Bayesian model that smooths the risk from neighboring regions and clearly accounts for population difference by using a Poisson distribution for ...
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Bayesian hierarchical models for misaligned data: a simulation study
... In this work, we considered the problem of combining information from different data sources focusing on spatially misaligned data. A hierarchical Bayesian model is used to convert the source information to ...
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A Bayesian Hierarchical Model For Longitudinal Data
... of Hierarchical Bayesian model analysis using WinBUGS the posterior mean and standard error for each regression coefficients and the between treatment covariance are also shown in the above ...This ...
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Time for a Change: a Tutorial for Comparing Multiple Classifiers Through Bayesian Analysis
... in Bayesian analysis? Paraphrasing Gelman et al. (2012): “in Bayesian analysis we usually do not have to worry about multiple ...does Bayesian Analysis mitigate false alarms? Gelman et ...a ...
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