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Myeonghun Yoo

Ewha Womans University

研究室紹介

Professor Myeonghun Yoo's research lab specializes in high-dimensional statistical modeling, with a focus on quantile regression, sparse estimation, and inference under complex data structures. The lab develops advanced methodologies for analyzing high-dimensional data with heterogeneous effects across conditional distributions, emphasizing regularization techniques, post-selection inference, and efficient computation for dependent or structured observations. Current research integrates statistical theory with optimization, aiming to bridge methodological innovation and practical application in large-scale data analysis.

high-dimensional statisticsquantile regressionregularizationpost-selection inferencesparse estimation

Research Overview

Papers
1
Total Citations
0
Papers (5y)
1
Primary Field

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
1total
2026
Citations per year (5y)
0total
2026

Selected Papers

1
1
other|0 citations·2026
High‐Dimensional Quantile Regression
Xinling Xie, Myeonghun Yu, Wen‐Xin Zhou, Kean Ming Tan
Wiley StatsRef: Statistics Reference Online

Abstract This article provides a selective overview of recent advances in high‐dimensional quantile regression, a framework that captures heterogeneous covariate effects across the conditional distribution. We synthesize methodological and theoretical developments in four major areas: regularization and sparse estimation, post‐selection inference, quantile modeling in complex data structures, and large‐scale analysis with dependent observations. The review highlights modern penalization techniqu

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