Empirical Bayesian inference in a nonparametric regression model

Koop, G.M. and Poirier, D.; Harvey, Andrew and Jan Koopman, Siem and Shephard, Neil, eds. (2005) Empirical Bayesian inference in a nonparametric regression model. In: State Space Models and Unobserved Components. Cambridge University Press, pp. 152-171. ISBN 052183595X (https://doi.org/10.2277/052183595X)

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.

ORCID iDs

Koop, G.M. ORCID: https://orcid.org/0000-0002-6091-378X

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• Item metadata

  Item type:	Book Section
  ID code:	7917
  Dates:	Date Event 2005 Published
  Subjects:	Social Sciences > Commerce Social Sciences > Economic Theory
  Department:	Strathclyde Business School > Economics
  Depositing user:	Strathprints Administrator
  Date deposited:	29 Apr 2009 15:37
  Last modified:	11 Nov 2024 14:33
  Related URLs:	Publisher http://dx.doi.org/10.2277/052183595X
  URI:	https://strathprints.strath.ac.uk/id/eprint/7917