Radojičić, U., Nordhausen, K., & Virta, J. (2026). Unsupervised linear discrimination using skewness. Journal of Multivariate Analysis, 211, Article 105524. https://doi.org/10.1016/j.jmva.2025.105524

Radojičić, U., Nordhausen, K., & Virta, J. (2025). Kurtosis-based projection pursuit for matrix-valued data. Annals of Statistics, 53(6), 2563–2591. https://doi.org/10.1214/25-AOS2555

Nordhausen, K., & Radojičić, U. (2025). Discussion to the paper ‘Robust Distance Covariance.’ International Statistical Review. https://doi.org/10.1111/insr.70013

Radojičić, U., & Virta, J. (2025). Dimension estimation in a spiked covariance model using high-dimensional data augmentation. Biometrika, 112(4), Article asaf052. https://doi.org/10.1093/biomet/asaf052

Mayrhofer, M., Radojičić, U., & Filzmoser, P. (2025). Robust And Interpretable Matrix-Variate Data Analysis. In CLADAG - VOC 2025 : 15th Scientific Meeting of the Classification and Data Analysis Group 1st International Scientific Joint Meeting of the Italian and Dutch/Flemish Classification Societies : BOOK OF ABSTRACTS (pp. 129–129).

Mayrhofer, M., Radojičić, U., & Filzmoser, P. (2025). Robust covariance estimation and explainable outlier detection for matrix-valued data. Technometrics, 67(3), 516–530. https://doi.org/10.1080/00401706.2025.2475781

Radojičić, U., Lietzen, N., Nordhausen, K., & Virta, J. (2025). Order Determination for Tensor-Valued Observations Using Data Augmentation. Journal of Computational and Graphical Statistics, 1–11. https://doi.org/10.1080/10618600.2025.2500977

Oguamalam, J., Radojičić, U., & Filzmoser, P. (2024). Minimum Regularized Covariance Trace Estimator and Outlier Detection for Functional Data. Technometrics, 66(4), 588–599. https://doi.org/10.1080/00401706.2024.2336542

Oguamalam, J., Radojicic, U., & Filzmoser, P. (2024). Robust covariance estimation and functional anomaly detection based on the Minimum Regularized Covariance Trace estimator. In PROGRAM AND ABSTRACTS - Austrian Statistical Days 2024. Austrian Statistical Days 2024, Wien, Austria.

Matys Grygar, T., Radojičić, U., Pavlu, I., Greven, S., Nešlehová, J. G., Tůmová, Š., & Hron, K. (2024). Exploratory functional data analysis of multivariate densities for the identification of agricultural soil contamination by risk elements. Journal of Geochemical Exploration, 259, Article 107416. https://doi.org/10.1016/j.gexplo.2024.107416

Mayrhofer, M., Radojicic, U., & Filzmoser, P. (2024). A minimum covariance determinant approach for matrix-variate data. In Statistische Woche 2024: Book of Abstracts (pp. 88–88).

Möttönen, J., Nordhausen, K., Oja, H., & Radojicic, U. (2024). The Asymptotic Properties of the One-Sample Spatial Rank Methods. In M. Barigozzi, S. Hörmann, & D. Paindaveine (Eds.), Recent Advances in Econometrics and Statistics: Festschrift in Honour of Marc Hallin (pp. 49–69). Springer. https://doi.org/10.1007/978-3-031-61853-6_3

Filzmoser, P., Mayrhofer, M., Radojicic, U., & Lewitschnig, H. (2023). Explainable outlier identification for matrix-valued observations. In Book of Abstracts : International Conference on Data Science : ICDS 2023 : Multidimensional Perspectives: From Statistical Learning to Data Science Applications (pp. 13–13).

Oguamalam, J., Radojicic, U., & Filzmoser, P. (2023). Functional Outlier Detection based on the Minimum Regularized Covariance Trace Estimator. In Book of abstracts: Joint conference of Data Science, Statistics & Visualisation and the European Conference on Data Analysis (pp. 102–102).

Oguamalam, J., Radojicic, U., & Filzmoser, P. (2023). Minimum Regularized Covariance Trace Estimator and Outlier Detection for Functional Data. In Book of Abstracs - Olomoucian Days of Applied Mathematics ODAM 2023 (pp. 57–57).

Archimbaud, A., Drmac, Z., Nordhausen, K., Radojičić, U., & Ruiz-Gazen, A. (2023). Numerical Considerations and a new implementation for invariant coordinate selection. SIAM JOURNAL ON MATHEMATICS OF DATA SCIENCE, 5(1), 97–121. https://doi.org/10.1137/22M1498759

Radojičić, U., Nordhausen, K., & Taskinen, S. (2022). Singular Spectrum Analysis. In Encyclopedia of Mathematical Geosciences. https://doi.org/10.1007/978-3-030-26050-7_294-1

Radojicic, U., Lietzen, N., Nordhausen, K., & Virta, J. (2021). Dimension Estimation in Two-Dimensional PCA. In 2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA). 12th Int´l Symposium on Image and Signal Processing and Analysis, Zagreb, Croatia. https://doi.org/10.1109/ispa52656.2021.9552114

Radojičić, U., & Nordhausen, K. (2021). Least Absolute Value. In Encyclopedia of Mathematical Geosciences. https://doi.org/10.1007/978-3-030-26050-7_177-1

Radojičić, U., Nordhausen, K., & Virta, J. (2021). Large-sample properties of blind estimation of the linear discriminant using projection pursuit. Electronic Journal of Statistics, 15(2). https://doi.org/10.1214/21-ejs1956

Radojičić, U., & Nordhausen, K. (2020). Non-Gaussian Component Analysis: Testing the Dimension of the Signal Subspace. In M. Maciak, M. Pesta, & M. Schindler (Eds.), Analytical Methods in Statistics (pp. 101–123). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-030-48814-7_6

Radojičić, U., Nordhausen, K., & Oja, H. (2020). Notion of Information and Independent Component Analysis. Applications of Mathematics, 65(3), 311–330. https://doi.org/10.21136/am.2020.0326-19