Bayesian inference for stationary points in Gaussian process regression models for event-related potentials analysis.

Yu, Cheng-Han; Li, Meng; Noe, Colin; Fischer-Baum, Simon; Vannucci, Marina

Yu, Cheng-Han; Li, Meng; Noe, Colin; Fischer-Baum, Simon; Vannucci, Marina.

Afiliación

Yu CH; Department of Mathematical and Statistical Sciences, Marquette University, Milwaukee, Wisconsin, USA.
Li M; Department of Statistics, Rice University, Houston, Texas, USA.
Noe C; Department of Psychological Science, Rice University, Houston, Texas, USA.
Fischer-Baum S; Department of Psychological Science, Rice University, Houston, Texas, USA.
Vannucci M; Department of Statistics, Rice University, Houston, Texas, USA.

Biometrics ; 79(2): 629-641, 2023 06.

Article en En | MEDLINE | ID: mdl-34997758

Asunto(s)

Electroencefalografía; Potenciales Evocados; Anciano; Humanos; Teorema de Bayes; Distribución Normal; Adulto Joven

Palabras clave

Bayesian inference; ERP data; Gaussian process; derivatives; semiparametric

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Electroencefalografía / Potenciales Evocados Tipo de estudio: Prognostic_studies Límite: Adult / Aged / Humans Idioma: En Revista: Biometrics Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

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