Background: In order to compute pattern statistics in computational biology a Markov model is commonly used to take into account the sequence composition. Usually its parameter mu...
We study a sequential variance reduction technique for Monte Carlo estimation of functionals in Markov Chains. The method is based on designing sequential control variates using s...
Mark-recapture models have for many years been used to estimate the unknown sizes of animal and bird populations. In this article we adapt a finite mixture mark-recapture model i...
We propose a two-state Markov chain model of degraded document images. The model generates random and burst noise to simulate isolated pixel reversal as well as blurring of a larg...
In macromodeling-based power estimation, circuit macromodels are created from simulations of synthetic input vector sequences. Fast generation of these sequences with all possible...