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Adaptive Polar Sampling: A New MC Technique for the Analysis of Ill-behaved Surfaces

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Author Info
Luc Bauwens (CORE, Université Catholique de Louvain)
Charles S. Bos () (Erasmus University Rotterdam)
Herman K. van Dijk () (Erasmus University Rotterdam)

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Abstract

Adaptive Polar Sampling is proposed as an algorithm where random drawings are directly generated from the target function (posterior) in all-but-one directions of the parameter space. The method is based on the mixed integration technique of Van Dijk, Kloek & Boender (1985) but extends this one by replacing the one-dimensional quadrature step by Monte Carlo simulation from this one-dimensional distribution function.
The method is particularly suited for the analysis of ill-behaved surfaces. An illustrative example shows the feasibility of the algorithm.

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Publisher Info
Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 98-071/4.

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Date of creation: 09 Jul 1998
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Handle: RePEc:dgr:uvatin:19980071

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Web page: http://www.tinbergen.nl/

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Related research
Keywords: Markov Chain Monte Carlo sampling Ill-behaved surfaces Polar coordinates

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  1. Kloek, Tuen & van Dijk, Herman K, 1978. "Bayesian Estimates of Equation System Parameters: An Application of Integration by Monte Carlo," Econometrica, Econometric Society, vol. 46(1), pages 1-19, January. [Downloadable!] (restricted)
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