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An Efficient Algorithm for Elastic I-optimal Design of Generalized Linear Models
TLDR
We consider the Elastic I-optimality as a prediction-oriented design criterion for generalized linear models, and develop efficient algorithms for such $\text{EI}$-optimal designs. Expand
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ORTHOGONAL BASES FOR POLYNOMIAL REGRESSION WITH DERIVATIVE INFORMATION IN UNCERTAINTY QUANTIFICATION
We discuss the choice of polynomial basis for approximation of uncertainty propagation through complex simulation models with capabilityto outputderivative information.Ourwork ispart of a largerExpand
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EI-Optimal Design: An Efficient Algorithm for Elastic I-optimal Design of Generalized Linear Models
TLDR
The generalized linear models (GLMs) are widely used in statistical analysis and the related design issues are undoubtedly challenging. Expand
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On I-Optimal Designs for Generalized Linear Models: An Efficient Algorithm via General Equivalence Theory
The generalized linear model plays an important role in statistical analysis and the related design issues are undoubtedly challenging. The state-of-the-art works mostly apply to design criteria onExpand
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Is a Transformed Low Discrepancy Design Also Low Discrepancy
Experimental designs intended to match arbitrary target distributions are typically constructed via a variable transformation of a uniform experimental design. The inverse distribution function isExpand
Financial contagion and contagion channels in the forex market: A new approach via the dynamic mixture copula-extreme value theory
We propose a new approach to the study of financial contagion and contagion channels in the forex market by using a dynamic mixture copula-extreme value theory (DMC-EVT) model. This method allowsExpand
Topics in statistical modeling and optimal design
A Maximin $\Phi_{p}$-Efficient Design for Multivariate GLM
Experimental designs for a generalized linear model (GLM) often depend on the specification of the model, including the link function, the predictors, and unknown parameters, such as the regressionExpand
A Discrepancy-Based Design for A/B Testing Experiments
  • Yiou Li, Xiao Huang, L. Kang
  • Computer Science, Mathematics
  • 25 January 2019
TLDR
The aim of this paper is to introduce a new design of experiment method for A/B tests in order to balance the covariate information in all treatment groups. Expand