Density estimators through Zero Variance Markov Chain Monte Carlo
A Markov Chain Monte Carlo method is proposed for the pointwise evaluation of a density whose normalizing constant is not known. This method was introduced in the physics literature by Assaraf et al (2007). Conditions for unbiasedness of the estimator are derived. A central limit theorem is also proved under regularity conditions. The new idea is tested on some toy-examples.
|Date of creation:||Mar 2011|
|Contact details of provider:|| Postal: Via Ravasi 2-21100 Varese|
Web page: http://www.uninsubria.it/uninsubria/facolta/econo.html
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:ins:quaeco:qf1108. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Segreteria Dipartimento)
If references are entirely missing, you can add them using this form.