The conditional 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.
An extension of the censored gaussian lasso estimator / Augugliaro, Luigi; Sottile, Gianluca; Vinciotti, Veronica. - (2019), pp. 39-46. (Intervento presentato al convegno SIS2019 tenutosi a Milano nel 18-21 June 2019).
An extension of the censored gaussian lasso estimator
Vinciotti, Veronica
2019-01-01
Abstract
The conditional 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.File in questo prodotto:
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