Autori:
Mueller, Peter ![](http://www.bncf.firenze.sbn.it/img/logo-bncf.jpg)
,
Quintana, Fernando A. ![](http://www.bncf.firenze.sbn.it/img/logo-bncf.jpg)
,
Page, Garritt ![](http://www.bncf.firenze.sbn.it/img/logo-bncf.jpg)
Titolo:
Nonparametric Bayesian inference in applicationsPeriodico:
Statistical methods & applications : Journal of the Italian Statistical SocietyAnno:
2018 - Volume:
27 - Fascicolo:
2 - Pagina iniziale:
175 - Pagina finale:
206Nonparametric Bayesian (BNP) inference is concerned with inference for infinite dimensional parameters, including unknown distributions, families of distributions, random mean functions and more. Better computational resources and increased use of massive automated or semi-automated data collection makes BNP models more and more common. We briefly review some of the main classes of models, with an emphasis on how they arise from applied research questions, and focus in more depth only on BNP models for spatial inference as a good example of a class of inference problems where BNP models can successfully address limitations of parametric inference.
Premi sulle icone
![](http://www.bncf.firenze.sbn.it/img/logo-bncf.jpg)
a fianco dei nomi per visualizzare i libri scritti dall'autore
X
Opere monografiche dal catalogo BNCF
SICI: 1618-2510(2018)27:2<175:NBIIA>2.0.ZU;2-T
Esportazione dati in Refworks (solo per utenti abilitati)
Record salvabile in Zotero
Biblioteche ACNP che possiedono il periodico