• 44 Citations
  • 4 h-Index
20092020
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Research Output 2009 2020

  • 44 Citations
  • 4 h-Index
  • 16 Article
  • 1 Comment/debate
  • 1 Letter
  • 1 Review article
Filter
Article
2020

Penetrance of different cancer types in families with Li-Fraumeni syndrome: A validation study using multicenter cohorts

Shin, S. J., Dodd-Eaton, E. B., Peng, G., Bojadzieva, J., Chen, J., Amos, C. I., Frone, M. N., Khincha, P. P., Mai, P. L., Savage, S. A., Ballinger, M. L., Thomas, D. M., Yuan, Y., Strong, L. C. & Wang, W., 2020 Jan 15, In : Cancer Research. 80, 2, p. 354-360 7 p.

Research output: Contribution to journalArticle

Li-Fraumeni Syndrome
Penetrance
Validation Studies
Sarcoma
Neoplasms
2019

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
2 Citations (Scopus)

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
2018
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

Principal quantile regression for sufficient dimension reduction with heteroscedasticity

Wang, C., Shin, S. J. & Wu, Y., 2018 Jan 1, In : Electronic Journal of Statistics. 12, 2, p. 2114-2140 27 p.

Research output: Contribution to journalArticle

Open Access
Sufficient Dimension Reduction
Heteroscedasticity
Quantile Regression
Reduction Method
Efficient Solution
1 Citation (Scopus)

Stability approach to selecting the number of principal components

Song, J. & Shin, S. J., 2018 Dec 1, In : Computational Statistics. 33, 4, p. 1923-1938 16 p.

Research output: Contribution to journalArticle

Principal Components
Principal component analysis
Linear transformations
Unsupervised learning
Principal Component Analysis
2017

A comparative study of the dose-response analysis with application to the target dose estimation

Shin, S. J. & Ghosh, S. K., 2017 Jan 2, In : Journal of Statistical Theory and Practice. 11, 1, p. 145-162 18 p.

Research output: Contribution to journalArticle

Dose-response
Comparative Study
Dose
Probability function
Response Function
1 Citation (Scopus)

A nonparametric survival function estimator via censored kernel quantile regressions

Shin, S. J., Zhang, H. H. & Wu, Y., 2017 Jan 1, In : Statistica Sinica. 27, 1, p. 457-478 22 p.

Research output: Contribution to journalArticle

Kernel Regression
Quantile Regression
Survival Function
Survival Time
Estimator
3 Citations (Scopus)

Penalized principal logistic regression for sparse sufficient dimension reduction

Shin, S. J. & Artemiou, A., 2017 Jul 1, In : Computational Statistics and Data Analysis. 111, p. 48-58 11 p.

Research output: Contribution to journalArticle

Sufficient Dimension Reduction
Logistic Regression
Logistics
Predictors
Central Subspace
4 Citations (Scopus)

Principal weighted support vector machines for sufficient dimension reduction in binary classification

Shin, S. J., Wu, Y., Zhang, H. H. & Liu, Y., 2017 Mar 1, In : Biometrika. 104, 1, p. 67-81 15 p.

Research output: Contribution to journalArticle

Open Access
Sufficient Dimension Reduction
Binary Classification
Support vector machines
Support Vector Machine
Sliced Inverse Regression
1 Citation (Scopus)

The cumulative Kolmogorov filter for model-free screening in ultrahigh dimensional data

Kim, A. K. H. & Shin, S. J., 2017 Jul 1, In : Statistics and Probability Letters. 126, p. 238-243 6 p.

Research output: Contribution to journalArticle

Screening
Filter
Slicing
Model
Demonstrate
2014
11 Citations (Scopus)

Probability-enhanced sufficient dimension reduction for binary classification

Shin, S. J., Wu, Y., Zhang, H. H. & Liu, Y., 2014 Sep 1, In : Biometrics. 70, 3, p. 546-555 10 p.

Research output: Contribution to journalArticle

Sufficient Dimension Reduction
Binary Classification
slicing
Slicing
Sliced Inverse Regression
5 Citations (Scopus)

Two-dimensional solution surface for weighted support vector machines

Shin, S. J., Wu, Y. & Zhang, H. H., 2014 Jan 1, In : Journal of Computational and Graphical Statistics. 23, 2, p. 383-402 20 p.

Research output: Contribution to journalArticle

Support Vector Machine
Regularization Parameter
Binary Classification
Optimal Parameter
Piecewise Linear
2009

Bootstrapping spatial median for location problems

Jhun, M. & Shin, S. J., 2009 Nov 1, In : Communications in Statistics: Simulation and Computation. 38, 10, p. 2123-2133 11 p.

Research output: Contribution to journalArticle

Bootstrapping
Location Problem
Sample mean
Covariance matrix
Simultaneous Confidence Intervals