Empirical Bayesian inference in a nonparametric regression model

G.M. Koop; D. Poirier; Andrew Harvey; Siem Jan Koopman; Neil Shephard

doi:10.2277/052183595X

Empirical Bayesian inference in a nonparametric regression model

G.M. Koop, D. Poirier, Andrew Harvey (Editor), Siem Jan Koopman (Editor), Neil Shephard (Editor)

Economics

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

Describes procedures for Bayesian estimation and testing in cross-sectional, panel data and nonparametric regression models. Non-parametric regression is a type of regression analysis in which the functional form of the relationship between the response variable and the associated predictor variables does not to be specified in order to fit a model to a set of data.

Original language	English
Title of host publication	State Space Models and Unobserved Components
Publisher	Cambridge University Press
Pages	152-171
Number of pages	19
ISBN (Print)	052183595X
DOIs	https://doi.org/10.2277/052183595X
Publication status	Published - 2005

Keywords

bayesian econometrics
semiparametric regression
non-parametric regression models

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10.2277/052183595X

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abstract = "Describes procedures for Bayesian estimation and testing in cross-sectional, panel data and nonparametric regression models. Non-parametric regression is a type of regression analysis in which the functional form of the relationship between the response variable and the associated predictor variables does not to be specified in order to fit a model to a set of data.",

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KW - semiparametric regression

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Empirical Bayesian inference in a nonparametric regression model

Abstract

Keywords

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