Estimating the granularity coefficient of a Potts-Markov random field within an Markov Chain Monte Carlo algorithm

In this section we construct an estimator that works well whenever the distribution of X is sufficiently spherical in the sense that a positive fraction of the eigenvalues of

Probabilities of errors for the single decoder: (solid) Probability of false negative, (dashed) Probability of false positive, [Down] Average number of caught colluders for the

A similar concept is developed in [13] for continuous time positive linear systems and is referred as to the proportional dynamics property for the transient measure concerned

A potentially clinically relevant decrease in faldaprevir exposure was observed when coadministered with efavirenz; this decrease can be managed using the higher of the 2

Under the assumption that neither the time gaps nor their distribution are known, we provide an estimation method which applies when some transi- tions in the initial Markov chain X

– MCMC yields Up component velocity uncertainties which are around [1.7,4.6] times larger than from CATS, and within the millimetre per year range

En outre, le raisonnement expérimental est souvent mis en avant dans le curriculum actuel de l'enseignement de la biologie, mais j'ai argumenté de l'importance à ne pas négliger

There was a breakthrough two years ago, when Baladi and Vall´ee [2] extended the previous method for obtaining limit distributions, for a large class of costs, the so-called