Graphical model selection for a particular class of continuous-time processes

Title:

Graphical model selection for a particular class of continuous-time processes

Creator:

Zorzi, Mattia

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:b9456bfd-1457-475c-b25d-a861c6cd443a
uuid:b9456bfd-1457-475c-b25d-a861c6cd443a
doi:10.14736/kyb-2019-5-0782

Subject:

entropy, optimization, sparse inverse covariance selection, regularization, and graphical models

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

{Graphical models provide an undirected graph representation of relations between the components of a random vector. In the Gaussian case such an undirected graph is used to describe conditional independence relations among such components. In this paper, we consider a continuous-time Gaussian model which is accessible to observations only at time T. We introduce the concept of infinitesimal conditional independence for such a model. Then, we address the corresponding graphical model selection problem, i. e. the problem to estimate the graphical model from data. Finally, simulation studies are proposed to test the effectiveness of the graphical model selection procedure.}

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Coverage:

782-801

Source:

Kybernetika | 2019 Volume:55 | Number:5

Harvested from:

CDK

Metadata only:

false