Bayesian Nonparametrics for Causal Inference and Missing Data

Bayesian Nonparametrics for Causal Inference and Missing Data voorzijde
Bayesian Nonparametrics for Causal Inference and Missing Data achterzijde
  • Bayesian Nonparametrics for Causal Inference and Missing Data voorkant
  • Bayesian Nonparametrics for Causal Inference and Missing Data achterkant

Bayesian nonparametric (BNP) methods can be used to flexibly model joint or conditional distributions, as well as functional relationships. These methods, along with causal and/or missingness assumptions, can be used with the g-formula to infer causal effects.

Specificaties
ISBN/EAN 9780367341008
Auteur Daniels, Michael J. (University of Florida, Gainesville, USA)
Uitgever Van Ditmar Boekenimport B.V.
Taal Engels
Uitvoering Gebonden in harde band
Pagina's 248
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