Results 21 to 30 of about 26,331 (262)
Portfolio optimisation using constrained hierarchical bayes models
It is well known that traditional mean-variance optimal portfolio delivers rather erratic and unsatisfactory out-of-sample performance due to the neglect of estimation errors.
Jiangyong Yin, Xinyi Xu
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Between-groups within-gene heterogeneity of residual variances in microarray gene expression data
Background The analysis of microarray gene expression data typically tries to identify differential gene expression patterns in terms of differences of the mathematical expectation between groups of arrays (e.g.
Varona Luis, Casellas Joaquim
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A Bayesian Alternative to Mutual Information for the Hierarchical Clustering of Dependent Random Variables. [PDF]
The use of mutual information as a similarity measure in agglomerative hierarchical clustering (AHC) raises an important issue: some correction needs to be applied for the dimensionality of variables.
Guillaume Marrelec +2 more
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Generalizing Variational Autoencoders with Hierarchical Empirical Bayes
Variational Autoencoders (VAEs) have experienced recent success as data-generating models by using simple architectures that do not require significant fine-tuning of hyperparameters. However, VAEs are known to suffer from over-regularization which can lead to failure to escape local maxima.
Wei Cheng +3 more
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Spatial hierarchical Bayes Small Area Model for disaggregated level crop acreage estimation
Crop area statistics in most of the states in India are provided based on complete enumeration or census approach. But, shortage of man power, failure of the primary and revenue staffs to devote adequate time and attention in collection and compilation ...
PRIYANKA ANJOY +2 more
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The ability to track the changes of the surrounding environment is critical for humans and animals to adapt their behaviors. In high-dimensional environments, the interactions between each dimension need to be estimated for better perception and decision
Changbo Zhu +5 more
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Background Uncertainty often affects molecular biology experiments and data for different reasons. Heterogeneity of gene or protein expression within the same tumor tissue is an example of biological uncertainty which should be taken into account when ...
Piergiorgi Paolo +4 more
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In this study, a new three-statement randomized response estimation method is proposed to improve the drawback that the maximum likelihood estimation method could generate a negative value to estimate the sensitive-nature proportion (SNP) when its true ...
Hua Xin +3 more
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SMALL AREA ESTIMATION WITH HIERARCHICAL BAYES FOR CROSS-SECTIONAL AND TIME SERIES SKEWED DATA
Small Area Estimation (SAE) is a method based on modeling for estimating small area parameters, that applies Linear Mixed Model (LMM) as its basic. It is conventionally solved with Empirical Best Linear Unbiased Prediction (EBLUP).
Titin Yuniarty +2 more
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Nghiên cứu này nhằm khám phá ưu tiên lựa chọn của người tiêu dùng Việt Nam đối với các thuộc tính của phương thức thanh toán dựa trên phương pháp phân tích kết hợp (Choice-Based Conjoint - CBC), bổ sung luận chứng về cơ chế đánh đổi trong hành vi chấp ...
Vo Quang Tri +2 more
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