Sparse Signal Shrinkage and Outlier Detection in High-Dimensional Quantile Regression With Variational Bayes

Statistics and its Interface- United States

doi 10.4310/sii.2020.v13.n2.a8

Full Text

Abstract

Available in

Date

Authors

Publisher

International Press of Boston

Related search

FIRST: Combining Forward Iterative Selection and Shrinkage in High Dimensional Sparse Linear Regression

Statistics and its Interface
Applied MathematicsStatisticsProbability
2009English

Semiparametric Quantile Regression With High-Dimensional Covariates

Statistica Sinica
UncertaintyStatisticsProbability
2012English

Outlier Detection for High-Dimensional Data

Biometrika
StatisticsProbabilityUncertaintyApplied MathematicsBiological SciencesAgriculturalMathematics
2015Danish

Outlier Detection in Linear Regression

Dutch

Quantile Regression in High-Dimension With Breaking

Journal of Statistical Theory and Applications
2013English

High Quantile Regression for Extreme Events

Journal of Statistical Distributions and Applications
UncertaintyComputer Science ApplicationsStatisticsProbability
2017English

Efficient Neighborhood Density Based Outlier Detection Inside a Sub Network With High Dimensional Data

Ingenierie des Systemes d'Information
Information Systems
2019English

Hyperspherical Sparse Approximation Techniques for High-Dimensional Discontinuity Detection

SIAM Review
Computational MathematicsApplied MathematicsTheoretical Computer Science
2016English

Assessing Quantile Prediction With Censored Quantile Regression Models

Biometrics
StatisticsGeneticsProbabilityMolecular BiologyBiochemistryApplied MathematicsMicrobiology ImmunologyBiological SciencesMedicineAgricultural
2016English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2026 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy