High Dimensional Data and Data Sciences

Jamotton, C., & Hainaut, D. (2026). A Multivariate Energy-Based Fairness Adjuster for Premiums. North American Actuarial Journal. Accepted/in-press. https://doi.org/10.1080/10920277.2026.2705183 (Original work published 2026)

Jamotton, C., & Hainaut, D. (2026). Latent Dirichlet Allocation for Structured Insurance Data. Annals of Data Science. Accepted/in-press. https://doi.org/10.1007/s40745-026-00674-8 (Original work published 2026)

Pircalabelu, E., & Bing, X. (2026). Overlapping clustering of time dependent variables for fMRI data. Journal of the Royal Statistical Society. Series C, Applied statistics. Submitted. (Original work published 2026)

Lederer, J., & von Sachs, R. (2026). Simultaneous estimation of stable parameters for multiple autoregressive processes from datasets of nonuniform sizes. Journal of Time Series Analysis, 47(2), 345-363. (Original work published 2026)

Jacquemain, A., Heuchenne, C., & Pircalabelu, E. (2024). A penalised bootstrap estimation procedure for the explained Gini coefficient. Electronic Journal of Statistics, 18(1), 247-300. https://doi.org/10.1214/23-EJS2200 (Original work published 2024)

Nezakati Rezazadeh, E., & Pircalabelu, E. (2024). Estimation and inference in sparse multivariate regression and conditional Gaussian graphical models under an unbalanced distributed setting. Electronic Journal of Statistics, 18(1), 599-652. https://doi.org/10.1214/23-EJS2193 (Original work published 2024)

Nezakati Rezazadeh, E., & Pircalabelu, E. (2023). Unbalanced distributed estimation and inference for the precision matrix in Gaussian graphical models. Statistics and Computing, 33, 47. https://doi.org/10.1007/s11222-023-10211-9 (Original work published 2023)

Pircalabelu, E., & Claeskens, G. (2023). Linear manifold modeling and graph estimation based on multivariate functional data with different coarseness scales. Journal of Computational and Graphical Statistics, 32(2), 378-387. https://doi.org/10.1080/10618600.2022.2108818 (Original work published 2023)