• 36 Citations
  • 4 h-Index
20092019
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Fingerprint Dive into the research topics where Seung Jun Shin is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 2 Similar Profiles
Sufficient Dimension Reduction Mathematics
Binary Classification Mathematics
Quantile Regression Mathematics
Variable Selection Mathematics
Slicing Mathematics
Logistic Regression Mathematics
Support Vector Machine Mathematics
Predictors Mathematics

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Research Output 2009 2019

  • 36 Citations
  • 4 h-Index
  • 15 Article
  • 1 Comment/debate
  • 1 Letter

A two-step approach for variable selection in linear regression with measurement error

Song, J. & Shin, S. J., 2019 Jan 1, In : Communications for Statistical Applications and Methods. 26, 1, p. 47-55 9 p.

Research output: Contribution to journalArticle

Open Access
Variable Selection
Measurement errors
Linear regression
Measurement Error
Covariates

Bayesian Semiparametric Estimation of Cancer-Specific Age-at-Onset Penetrance With Application to Li-Fraumeni Syndrome

Shin, S. J., Yuan, Y., Strong, L. C., Bojadzieva, J. & Wang, W., 2019 Apr 3, In : Journal of the American Statistical Association. 114, 526, p. 541-552 12 p.

Research output: Contribution to journalArticle

Semiparametric Estimation
Bayesian Estimation
Cancer
Competing Risks Model
Competing Risks
1 Citation (Scopus)

Principal weighted logistic regression for sufficient dimension reduction in binary classification

Kim, B. & Shin, S. J., 2019 Jun 1, In : Journal of the Korean Statistical Society. 48, 2, p. 194-206 13 p.

Research output: Contribution to journalArticle

Sufficient Dimension Reduction
Binary Classification
Logistic Regression
Reduction Method
Inverse Regression

Quantile-slicing estimation for dimension reduction in regression

Kim, H., Wu, Y. & Shin, S. J., 2019 Jan 1, In : Journal of Statistical Planning and Inference. 198, p. 1-12 12 p.

Research output: Contribution to journalArticle

Slicing
Dimension Reduction
Quantile
Sufficient Dimension Reduction
Regression
1 Citation (Scopus)

Hierarchically penalized quantile regression with multiple responses

Kang, J., Shin, S. J., Park, J. & Bang, S., 2018 Dec 1, In : Journal of the Korean Statistical Society. 47, 4, p. 471-481 11 p.

Research output: Contribution to journalArticle

Penalized Regression
Multiple Responses
Quantile Regression
Sparsity
Oracle Property