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unbiased estimation of log-normalising constants

October 16, 2018

Maxime Rischard, Pierre Jacob, and Natesh Pillai [warning: both of whom are co-authors and friends of mine!] have just arXived a paper on the use of path sampling (a.k.a., thermodynamic integration) for log-constant unbiased approximation and the resulting consequences on Bayesian model comparison by X validation. If the goal is the estimation of the log […]

normalising constants of G-Wishart densities

June 28, 2017

Abdolreza Mohammadi, Hélène Massam, and Gérard Letac arXived last week a paper on a new approximation of the ratio of two normalising constants associated with two G-Wishart densities associated with different graphs G. The G-Wishart is the generalisation of the Wishart distribution by Alberto Roverato to the case when some entries of the matrix are […]

estimating normalising constants [mea culpa?!]

May 28, 2014

“The basic idea is to estimate the parameters by learning to discriminate between the data x and some artificially generated noise y.” In the sequel of this popular earlier post of mine on [not] estimating normalising constants, Simon Barthelmé and Nicolas Chopin pointed me to recent papers by Michael Gutmann and Aapo Hyvaärinen on this […]

where did the normalising constants go?! [part 2]

March 12, 2014

Coming (swiftly and smoothly) back home after this wonderful and intense week in Banff, I hugged my loved ones,  quickly unpacked, ran a washing machine, and  then sat down to check where and how my reasoning was wrong. To start with, I experimented with a toy example in R: and (of course!) it produced the […]

where did the normalising constants go?! [part 1]

March 11, 2014

When listening this week to several talks in Banff handling large datasets or complex likelihoods by parallelisation, splitting the posterior as and handling each term of this product on a separate processor or thread as proportional to a probability density, then producing simulations from the mi‘s and attempting at deriving simulations from the original product, […]