On pointwise optimality of Bayes factor wavelet regression estimators

Natalia Bochkina; Theofanis Sapatinas

On pointwise optimality of Bayes factor wavelet regression estimators

Natalia Bochkina^*, Theofanis Sapatinas

^*Corresponding author for this work

School of Mathematics

Research output: Contribution to journal › Article › peer-review

Abstract

We investigate the theoretical performance of Bayes factor estimators at a single point in wavelet regression models with independent and identically distributed errors that are not necessarily normally distributed. We compare these estimators in terms of their frequentist pointwise optimality in Besov spaces for certain combinations of error and prior distributions.

Original language	English
Pages (from-to)	513-541
Number of pages	29
Journal	Sankhya A
Volume	68
Issue number	4
Publication status	Published - 1 Dec 2006

Keywords / Materials (for Non-textual outputs)

Bayesian inference
Besov spaces
Nonparametric regression
Optimality
Pointwise risk
Wavelets

Cite this

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title = "On pointwise optimality of Bayes factor wavelet regression estimators",

abstract = "We investigate the theoretical performance of Bayes factor estimators at a single point in wavelet regression models with independent and identically distributed errors that are not necessarily normally distributed. We compare these estimators in terms of their frequentist pointwise optimality in Besov spaces for certain combinations of error and prior distributions.",

keywords = "Bayesian inference, Besov spaces, Nonparametric regression, Optimality, Pointwise risk, Wavelets",

author = "Natalia Bochkina and Theofanis Sapatinas",

year = "2006",

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T1 - On pointwise optimality of Bayes factor wavelet regression estimators

AU - Bochkina, Natalia

AU - Sapatinas, Theofanis

PY - 2006/12/1

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N2 - We investigate the theoretical performance of Bayes factor estimators at a single point in wavelet regression models with independent and identically distributed errors that are not necessarily normally distributed. We compare these estimators in terms of their frequentist pointwise optimality in Besov spaces for certain combinations of error and prior distributions.

AB - We investigate the theoretical performance of Bayes factor estimators at a single point in wavelet regression models with independent and identically distributed errors that are not necessarily normally distributed. We compare these estimators in terms of their frequentist pointwise optimality in Besov spaces for certain combinations of error and prior distributions.

KW - Bayesian inference

KW - Besov spaces

KW - Nonparametric regression

KW - Optimality

KW - Pointwise risk

KW - Wavelets

UR - https://www.scopus.com/pages/publications/66249095680

M3 - Article

AN - SCOPUS:66249095680

SN - 0972-7671

VL - 68

SP - 513

EP - 541

JO - Sankhya A

JF - Sankhya A

IS - 4

ER -

On pointwise optimality of Bayes factor wavelet regression estimators

Abstract

Keywords / Materials (for Non-textual outputs)

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