Bayesian Semiparametric Multivariate Density Deconvolution.

Sarkar, Abhra; Pati, Debdeep; Chakraborty, Antik; Mallick, Bani K; Carroll, Raymond J

Sarkar, Abhra; Pati, Debdeep; Chakraborty, Antik; Mallick, Bani K; Carroll, Raymond J.

Afiliação

Sarkar A; Department of Statistical Science, Duke University, Durham, NC 27708-0251, USA, abhra.sarkar@duke.edu.
Pati D; Department of Statistics, Florida State University, Tallahassee, FL 32306-4330, USA, debdeep@stat.fsu.edu.
Chakraborty A; Department of Statistics, Texas A&M University, 3143 TAMU, College Station, TX, 77843-3143 USA, antik@stat.tamu.edu.
Mallick BK; Department of Statistics, Texas A&M University, 3143 TAMU, College Station, TX 77843-3143, USA, bmallick@stat.tamu.edu.
Carroll RJ; Department of Statistics, Texas A&M University, 3143 TAMU, College Station, TX 77843-3143, USA, and School of Mathematical and Physical Sciences, University of Technology Sydney, Broadway NSW 2007, Australia, carroll@stat.tamu.edu.

J Am Stat Assoc ; 113(521): 401-416, 2018.

Article em En | MEDLINE | ID: mdl-30078920

Palavras-chave

B-splines; Conditional heteroscedasticity; Latent factor analyzers; Measurement errors; Mixture models; Multivariate density deconvolution; Regularization; Shrinkage

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: J Am Stat Assoc Ano de publicação: 2018 Tipo de documento: Article

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