Registro de evidencia del método

MCMC with missing data

MCMC with missing data is a Bayesian computational strategy that treats unobserved values as additional unknown parameters. By alternating between sampling the missing values from their predictive distribution and sampling the model parameters from their posterior, the algorithm produces a valid joint posterior that fully accounts for uncertainty introduced by the missingness.

Sources recorded, not reviewed

Registro de origen

Citas copiadas textualmente del registro de origen del método. No se infiere ninguna verificación a nivel de afirmación de ellas.

Markov Chain Monte Carlo with Missing Data

Registro del método taxonómico · bayesian / bayesian

Little, R. J. A. & Rubin, D. B. (2002). Statistical Analysis with Missing Data (2nd ed.). Wiley. · ISBN 978-0471183860
Tanner, M. A. & Wong, W. H. (1987). The calculation of posterior distributions by data augmentation. Journal of the American Statistical Association, 82(398), 528-540. · DOI 10.1080/01621459.1987.10478458

Abrir método completo

Afirmaciones curadas

Afirmaciones persistidas en el libro mayor de evidencia, cada una con su propia evaluación.

Aún no hay afirmaciones curadas

Esta vista no inventa una evaluación de afirmación si el libro mayor no tiene ninguna.

Métodos relacionados

Generado a partir del grafo de métodos y mostrado como relaciones sugeridas por la máquina; no se infiere ninguna afirmación de evidencia.

Same method familyBayesian Hierarchical Modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketBayesian Inference with Missing Datamachine-suggested · Relational suggestion, not evidence.Taxonomic bucketGibbs Samplingmachine-suggested · Relational suggestion, not evidence.Same method familyHamiltonian Monte Carlomachine-suggested · Relational suggestion, not evidence.Same method familyMetropolis-Hastings Algorithmmachine-suggested · Relational suggestion, not evidence.See alsoMultiple Imputationmachine-suggested · Relational suggestion, not evidence.