Koop, G.M. and Poirier, D. (2005) Empirical Bayesian inference in a nonparametric regression model. In: State Space Models and Unobserved Components. Cambridge University Press, pp. 152-171. ISBN 052183595X
Full text not available in this repository. (Request a copy from the Strathclyde author)Official URL: http://dx.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.
| Item type: | Book Section |
|---|---|
| ID code: | 7917 |
| Keywords: | bayesian econometrics, semiparametric regression, non-parametric regression models, Commerce, Economic Theory |
| Subjects: | Social Sciences > Commerce Social Sciences > Economic Theory |
| Department: | Strathclyde Business School > Economics |
| Related URLs: | |
| Depositing user: | Strathprints Administrator |
| Date Deposited: | 29 Apr 2009 16:37 |
| Last modified: | 12 Mar 2012 10:48 |
| URI: | http://strathprints.strath.ac.uk/id/eprint/7917 |
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