ADJUSTED REGULARIZATION IN LATENT GRAPHICAL MODELS: APPLICATION TO MULTIPLE-NEURON SPIKE COUNT DATA.

Vinci, Giuseppe; Ventura, Valérie; Smith, Matthew A; Kass, Robert E

Vinci, Giuseppe; Ventura, Valérie; Smith, Matthew A; Kass, Robert E.

Afiliación

Vinci G; Rice University, Department of Statistics, Duncan Hall, 6100 Main St, Houston, 77005, TX, USA.
Ventura V; Carnegie Mellon University, Department of Statistics, Baker Hall 132, 5000 Forbes Avenue, Pittsburgh, 15203, PA, USA.
Smith MA; Center for the Neural Basis of Cognition.
Kass RE; University of Pittsburgh, Department of Ophthalmology, Eye and Ear Institute, Room 914 203 Lothrop St., Pittsburgh, PA 15213, USA.

Ann Appl Stat ; 12(2): 1068-1095, 2018 Jun.

Article en En | MEDLINE | ID: mdl-31772696

Palabras clave

Bayesian inference; Gaussian graphical models; Gaussian scale mixture; Poisson-lognormal; Primary 60K35, 60K35; high dimensionality; lasso; latent variable models; macaque prefrontal cortex; macaque visual cortex; secondary 60K35; sparsity; spike-counts

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Ann Appl Stat Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos

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