Adaptive polar sampling: a new MC technique for the analysis of ill behaved surfaces
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.
|Keywords||Ill-behaved surfaces, Markov Chain Monte Carlo sampling, Polar coordinates|
Bauwens, L., Bos, C.S., & van Dijk, H.K.. (1998). Adaptive polar sampling: a new MC technique for the analysis of ill behaved surfaces (No. EI 9822). Retrieved from http://hdl.handle.net/1765/1550