Bahadır Yüzbaşı

STATISTICS · ECONOMETRICS · DATA SCIENCE

Making structure visible in complex data.

Reliable inference, learning and prediction for high-dimensional, spatial and functional data.

I am a Professor of Statistics and Econometrics in the Department of Econometrics at İnönü University. My research focuses on reliable estimation and variable selection for high-dimensional and complex data. I combine shrinkage, pretest and penalized regression methods with statistical learning and spatial and functional data analysis. My recent work examines variable selection with scaled group lasso and shrinkage estimation in geographically weighted regression, including an application to digital platform pricing.

In the TÜBİTAK 1001 project I lead, we aim to model heterogeneity in big spatial data using explainable machine learning. In our completed TÜBİTAK 3005 project, we studied migration dynamics in Van using geographically weighted regression. I support theoretical methods with simulation, real-data analysis and reproducible research tools developed in R, Python and C++.

Selected publications TÜBİTAK 1001 project Download CV

ACADEMIC IMPACT

Research at a glance

ISI

Elected Member since 2023

1001

TÜBİTAK research project · 2026

R · Python · C++

Open-source research software

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RESEARCH & LEARNING

Methods to use. Ideas to explore.

R · PYTHON · C++

Research software

Packages for regularization, spatial models and statistical computing.

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Books & learning resources

Statistics, econometrics and linear algebra, from foundations to applications.

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Package websites softridge scaleCorrection emaxProjection gwrs AdaReFun sglasso lambertReg rbridge LHWL HDMaxShrink BernoulliRuns ShapeAdaptiveEN

FEATURED WORK

Books

All books

2023

Post-Shrinkage Strategies in Statistical and Machine Learning for High Dimensional Data

Syed Ejaz Ahmed, Feryaal Ahmed, and Bahadir Yüzbaşı

2023

DOI

Publisher page

Reviews in international journals

Selected publications

All publications

2026

Collinear Groupwise Selection via Scaled Group Lasso

Bahadır Yüzbaşı and Jiguo Cao

The American Statistician, 2026

SCIE; Q1 (JCR 2025); published online 17 September 2026; TÜBİTAK-supported research

DOI
Shrinkage estimation in geographically weighted regression with applications to digital platform pricing

Bahadır Yüzbaşı, S. Ejaz Ahmed, and Shuangzhe Liu

Spatial Statistics, 2026

SCIE; Q1 (JCR 2025)

DOI

2021

Penalized regression via the restricted bridge estimator

Bahadır Yüzbaşı, Mohammad Arashi, and Fikri Akdeniz

Soft Computing, Jul 2021

SCIE; Q3 (CV)

DOI

2020

Shrinkage Estimation Strategies in Generalised Ridge Regression Models: Low/High‐Dimension Regime

Bahadır Yüzbaşı, Mohammad Arashi, and S. Ejaz Ahmed

International Statistical Review, Apr 2020

SCIE; Q1 (CV)

Abs DOI

Summary In this study, we suggest pretest and shrinkage methods based on the generalised ridge regression estimation that is suitable for both multicollinear and high‐dimensional problems. We review and develop theoretical results for some of the shrinkage estimators. The relative performance of the shrinkage estimators to some penalty methods is compared and assessed by both simulation and real‐data analysis. We show that the suggested methods can be accounted as good competitors to regularisation techniques, by means of a mean squared error of estimation and prediction error. A thorough comparison of pretest and shrinkage estimators based on the maximum likelihood method to the penalty methods. In this paper, we extend the comparison outlined in his work using the least squares method for the generalised ridge regression.
Ridge-type pretest and shrinkage estimations in partially linear models

Bahadır Yüzbaşı, S. Ejaz Ahmed, and Dursun Aydın

Statistical Papers, Apr 2020

SCIE; Q3 (CV); TÜBİTAK-supported research

DOI

2016

Big data analytics: integrating penalty strategies

S. Ejaz Ahmed and Bahadır Yüzbaşı

International Journal of Management Science and Engineering Management, 2016

DOI
Shrinkage and penalized estimation in semi-parametric models with multicollinear data

Bahadır Yüzbaşı and S. Ejaz Ahmed

Journal of Statistical Computation and Simulation, Nov 2016

SCIE; Q2 (CV); TÜBİTAK-supported research

DOI