Statistical linearization based dimension reduction approach
A statistical approach to equivalent linearization with application to performance based engineering
... Another approach is to modify the capacity spectrum so that there are not multiple solutions. This would require performing a retrofit procedure on the structure. 5. The new procedure can clearly give insight into ...
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Some statistical methods for dimension reduction
... 17 In order to estimate the canonical correlations and canonical vectors of the population, we first estimate by the sample covariance matrix followed by the computation of the eigenvalues and eigenvectors of the ...
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Dimension estimation in sufficient dimension reduction: A unifying approach
... Sufficient Dimension Reduction (SDR) in regression comprises the estimation of the dimension of the smallest (central) dimension reduction subspace and its basis ...methods based ...
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A surrogate modelling approach based on nonlinear dimension reduction for uncertainty quantification in groundwater flow models
... dimensionality reduction for the input and/or output space can be ...dimensionality reduction on the response in order to render a GP model tractable (independent learning of a small number of PCA ...
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LDR: A Package for Likelihood-Based Sufficient Dimension Reduction
... Keywords: dimension reduction, inverse regression, principal ...Many statistical problems deal with the study of the conditional distribution of a response Y given a vector of predictors X ∈ R p or ...
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A Method of Web Page Classification Based on Feature Dimension Reduction
... elaborating the theme”, summary statements appear in web content page [8]. The rules show that the features in different positions, and its roles are not the same, although some of the features of tf is not high, it can ...
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Time series social network visualization based on dimension reduction
... data-mining based approach for dimensionality reduction in social ...new dimension reduction approach that is based on developing an SVD algorithm by relying on select ...
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Third-order statistical linearization-based approach to derive equivalent linear properties of bilinear hysteretic systems for seismic response spectrum analysis
... A salient feature of the thus obtained ELPs is that they are explicitly associated with both the pre-specified response spectrum and the considered bilinear system. In this respect, it is possible to obtain reliable ...
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Dimension Reduction Regression in R
... the dimension ' based on dimension reduction ...of dimension reduction methods with existing statistical methods that are not readily available in Xlisp-Stat, and hence in ...
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Topics in Multivariate Time Series Analysis: Statistical Control, Dimension Reduction Visualization and Their Business Applications
... The purpose of this research is to describe a graphical data analytic method that may help elucidate certain structural properties of multiple time series data, both temporary and contemporary. As indicated, the ...
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Statistical linearization based estimation of the peak response of nonlinear systems subject to the EC8 design spectrum
... stochastic approach is proposed to obtain reliable estimates of the peak response of nonlinear systems to excitations specified via a response/ design seismic ...the statistical linearization method ...
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H}istogram Partitioning for Feature Vector Dimension Reduction in Bins Approach for {CBIR
... The approach used is called bins approach; designed and implemented using image histogram ...are based on the variations used in the techniques to extract the image ...are based on the ...
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Fast and Effective Techniques for LWIR Radiative Transfer Modeling: A Dimension Reduction Approach
... perform dimension reduction on the transmittance, upwelling radiance, and downwelling radiance (TUD) data to create high accuracy atmospheric estimates with lower computational cost than RT ...this ...
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Mixed Elastic Modeling of Multilayer Composite Plates by Using Dimension Reduction Approach
... used dimension reduction method for boundary value ...sional reduction method for elasticity plate on an un- bounded ...used reduction approach based on discretization methods ...
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Cost-based reweighting for Principal Lq SVM for sufficient dimension reduction
... As with PSVM this algorithm corresponds to the LVR approach. One can easily adjust the algorithm accordingly to fit the OVA approach. There are two things we need to address in the estimation part. The ...
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A Statistical, Grammar Based Approach to Microplanning
... Entity Chaining Features. These features characterize the distribution of discourse entities in the query linearization. We use three binary features to capture cases where R i − 1 and R i , R i − 2 and R i , and ...
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Statistical learning methods for multi-omics data integration in dimension reduction, supervised and unsupervised machine learning
... = 0.723 - 0.759). In contrast, we also compared three mega-analysis and three single study analysis approaches. In mega-analysis approaches, the three training studies are normalized and combined into one study to ...
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A Study of Sufficient Dimension Reduction Methods
... structure dimension d in the PKQR, we employ the four-fold CVBIC approach and select an optimal ρ as ...methods. Based on the distance measurements and scatter plots, we see that PQR achieves a ...
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The Dual Central Subspaces in dimension reduction
... sufficient dimension reduction of two multivariate random ...our approach provides a dimension reduction of both vectors without requiring the dimensions of the reduction to be ...
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Dimension reduction based on canonical correlation
... There is severe collinearity in the predictors in Case 7. The tests for dimen- sionality are hardly affected by collinearity, even though the estimated CANCOR direction is unable to choose between (1, 1, 0, 0, 0) and (0, ...
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