The covariate adjusted glasso is one of the most used estimators for inferring genetic networks. Despite its diffusion, there are several fields in applied research where the limits of detection of modern measurement technologies make the use of this estimator theoretically unfounded, even when the assumption of a multivariate Gaussian distribution is satisfied. In this paper we propose an extension to censored data.
Luigi Augugliaro, Gianluca Sottile, Angelo Mineo (2021). SPARSE INFERENCE IN COVARIATE ADJUSTED CENSORED GAUSSIAN GRAPHICAL MODELS. In CLADAG 2021 BOOK OF ABSTRACTS AND SHORT PAPERS (pp. 251-254) [10.36253/978-88-5518-340-6].
SPARSE INFERENCE IN COVARIATE ADJUSTED CENSORED GAUSSIAN GRAPHICAL MODELS
Luigi Augugliaro
Primo
;Gianluca SottileSecondo
;Angelo MineoUltimo
2021-01-01
Abstract
The covariate adjusted glasso is one of the most used estimators for inferring genetic networks. Despite its diffusion, there are several fields in applied research where the limits of detection of modern measurement technologies make the use of this estimator theoretically unfounded, even when the assumption of a multivariate Gaussian distribution is satisfied. In this paper we propose an extension to censored data.
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