The Institute for Statistics and Mathematics is pleased to invite you to the next research seminar, taking place on campus:

Alessandro Casa (Faculty of Economics and Management, Free University of Bozen-Bolzano)
Truncated Pairwise Likelihood for Sparse High-Dimensional Covariance Estimation
Wednesday, May 14, 2025, 17:15, in Building D4, Room D4.0.127.

Abstract: The estimation of covariance structure in high-dimensional settings is a critical yet complex task. Pairwise likelihood provides a computationally feasible approximation to the full likelihood by considering bivariate margins, and in models like the multivariate normal, it can retain statistical efficiency. To address the challenge of estimating sparse high-dimensional covariance matrices, we introduce a novel method based on maximising a /truncated pairwise likelihood/. This approach selectively incorporates only those pairwise likelihood terms that correspond to nonzero covariance entries. The truncation is achieved by minimising the L2-distance between the score functions of the pairwise and full likelihoods, coupled with an L1-penalty to promote sparsity at the component level. In contrast to parameter-wise regularisation, our method directly selects relevant pairwise likelihood objects, thus preserving the unbiasedness of the estimating equations. We theoretically show that our selection procedure is consistent even as the dimensionality increases exponentially, and the resulting estimator converges to the oracle maximum likelihood estimator. The efficacy and robustness of our proposed method are supported by empirical results on synthetic and real-world datasets.

We aim to stream all on-campus talks via Zoom. A direct link to the stream will be posted on our website.

For further information and the seminar schedule, please see:
www.wu.ac.at/en/statmath/research/resseminar