My main research is in high-dimensional statistics. In particular, I am interested in
causal inference
missing data problems
variable selection
covariance / inverse covariance matrix estimation
graphical models
genetic prediction
robust estimation, etc.
Publications:
Vahe Avagyan, Martin P. Boer, Junita Solin, Aalt D. J. van Dijk, Daniela Bustos-Korts, Bart-Jan van Rossum, Jip J. C. Ramakers, Fred van Eeuwijk, Willem Kruijer . ”Penalized factorial regression as a flexible and computationally attractive reaction norm model for prediction in the presence of G x E” (2025), Theoretical and Applied Genetics, 138 (88). Link
Francesco Orsi, Vahe Avagyan. ”Built environment, lifestyle and carbon emissions: insights from an eight-week app-based survey in the Province of Utrecht (Netherlands)”. Urban Climate, 52, 101744 . Link
Vahe Avagyan. "Precision matrix estimation using penalized Generalized D-trace loss" (2022). Test, 31, 950-967, Link
Vahe Avagyan, Stijn Vansteelandt. "Stable IPW estimation for longitudinal studies" (2021). Scandinavian Journal of Statistics, 48, 1046–1067. Link
Alberto Brini, Vahe Avagyan, Ric De Vos, Jack Vossen, Edwin van den Heuvel, Jasper Engel. "Improved one-class modelling of high-dimensional metabolomics data via eigenvalue-shrinkage" (2021). Metabolites, 11 (4), 237. Link
Vahe Avagyan, Stijn Vansteelandt. "High-Dimensional inference for the average treatment effect under model misspecification using penalised bias-reduced double-robust estimation" (2021), Biostatistics and Epidemiology, 6 (2), 221-238. Link
Oliver Dukes, Vahe Avagyan, Stijn Vansteelandt. "Doubly robust tests of exposure effects under high-dimensional confounding" (2020), Biometrics, 76, 1190–1200 . Link
Vahe Avagyan, Xiaoling Mei. "Precision matrix estimation under data contamination with an application to minimum variance portfolio selection" (2019), Communications in Statistics - Simulation and Computation, 51 (4), 1381-1400 Link
Vahe Avagyan. "D-trace estimation of a precision matrix with eigenvalue control" (2019), Communications in Statistics - Simulation and Computation, 50 (4), 1231-1247 . Link
Vahe Avagyan, Andrés M. Alonso and Francisco J. Nogales. "D-trace Estimation of a precision matrix using adaptive lasso penalties" (2018), Advances in Data Analysis and Classification, 12 (2), 425-447. Link
Vahe Avagyan, Andrés M. Alonso and Francisco J. Nogales. "Improving the graphical lasso estimation for the precision matrix through roots of the sample covariance matrix" (2017), Journal of Computational and Graphical Statistics, 26 (4), 865-872. Link
Packages:
Willem Kruijer, Bart-Jan van Rossum, Vahe Avagyan. "factReg: Multi-Environment Genomic Prediction with Penalized Factorial Regression" (2023). Link