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On BIC's Selection Consistency for Discriminant Analysis
BIC Discriminant Analysis Selection Consistency
2016/1/19
Linear and quadratic discriminant analysis are two very useful classification methods, for which the problem of variable selection is of fundamental impor-tance. To this end, a BIC-type selection crit...
Robust efficient frontier analysis with a separable uncertainty model
Robust efficient frontier analysis separable uncertainty model
2015/7/10
Mean-variance (MV) analysis is often sensitive to model mis-specification or uncertainty, meaning that the MV efficient portfolios constructed with an estimate of the model parameters (i.e., the expec...
Probabilistic principal component analysis (PPCA) seeks a low dimensional representation of a data set in the presence of independent spherical Gaussian noise, Sigma = (sigma^2)*I. The maximum likelih...
Reproducing kernels for spaces of zero mean functions. Application to sensitivity analysis
Kernel Methods Global Sensitivity Analysis Sobol-Hoeffding Decomposition
2011/7/6
Given a Reproducing Kernel Hilbert Space (H, h., .i) of real-valued functions and a suitable measure \mu over the source space, we decompose H as sum of a subspace of centered functions for {\mu} and ...
Selection models with monotone weight functions in meta analysis
global constrained optimization meta analysis monotone non-increasing selection bias
2011/3/24
Publication bias, the fact that studies identified for inclusion in a meta analysis do not represent all studies on the topic of interest, is commonly recognized as a threat to the validity of the res...
Causality as a unifying approach between activation and connectivity analysis of fMRI data
Causality activations functional connectivity fMRI
2011/3/24
This paper indicates causality as the tool that unifies the analysis of both activations and connectivity of brain areas, obtained with fMRI data. Causality analysis is commonly applied to study conne...
Joint and Individual Variation Explained (JIVE) for Integrated Analysis of Multiple Datatypes
Vertical integration Multi-block data Principal Component
2011/3/24
Research in a number of fields now requires the analysis of "multi-block" data, in which multiple high-dimensional, and fundamentally disparate, datatypes are available for a common set of objects. In...
Joint and Individual Variation Explained (JIVE) for Integrated Analysis of Multiple Datatypes
Vertical integration Multi-block data Principal Component Analysis
2011/3/23
Research in a number of fields now requires the analysis of "multi-block" data, in which multiple high-dimensional, and fundamentally disparate, datatypes are available for a common set of objects. In...
Asymptotic distributions and subsampling in spectral analysis for almost periodically correlated time series
α-mixing properties almost periodically correlated time series consistency spectral analysis subsampling
2011/3/21
The aim of this article is to establish asymptotic distributions and consistency of subsampling for spectral density and for magnitude of coherence for non-stationary, almost periodically correlated t...