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Sparse semiparametric discriminant analysis (Q2256757)

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Language	Label	Description	Also known as
English	Sparse semiparametric discriminant analysis	scientific article

Statements

scholarly article

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Sparse semiparametric discriminant analysis (English)

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Journal of Multivariate Analysis

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publication date

20 February 2015

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full work available at URL

https://arxiv.org/abs/1304.4983

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zbMATH Keywords

Gaussian copulas

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linear discriminant analysis

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high-dimension asymptotics

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semiparametric model

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describes a project that uses

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MaRDI profile type

MaRDI publication profile

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Adapting to unknown sparsity by controlling the false discovery rate

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Simultaneous analysis of Lasso and Dantzig selector

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A Direct Estimation Approach to Sparse Linear Discriminant Analysis

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Estimation of copula-based semiparametric time series models

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Efficient Estimation of Semiparametric Multivariate Copula Models

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Least angle regression. (With discussion)

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High-dimensional classification using features annealed independence rules

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A Road to Classification in High Dimensional Space: The Regularized Optimal Affine Discriminant

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Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties

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Classifier technology and the illusion of progress

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Efficient estimation in the bivariate normal copula model: Normal margins are least favourable

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Discriminant analysis through a semiparametric model

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High-dimensional semiparametric Gaussian copula graphical models

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A unified approach to model selection and sparse recovery using regularized least squares

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A direct approach to sparse discriminant analysis in ultra-high dimensions

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High-dimensional graphs and variable selection with the Lasso

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Sparse linear discriminant analysis by thresholding for high dimensional data

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Multivariate Dispersion Models Generated From Gaussian Copula

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DALASS: variable selection in discriminant analysis via the LASSO

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Semiparametric estimation in copula models

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On the conditions used to prove oracle results for the Lasso

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Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$-Constrained Quadratic Programming (Lasso)

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Penalized Classification using Fisher’s Linear Discriminant

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Regularized rank-based estimation of high-dimensional nonparanormal graphical models

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Nearly unbiased variable selection under minimax concave penalty

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The Adaptive Lasso and Its Oracle Properties

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Regularization and Variable Selection Via the Elastic Net

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Identifiers

zbMATH Open document ID

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Mathematics Subject Classification ID

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zbMATH DE Number

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10.1016/J.JMVA.2014.12.009

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Sitelinks

Mathematics(1 entry)

mardi Publication:2256757

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