Comparing sweep strategies for stochastic relaxation
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Abstract
The rate of convergence of various sweep strategies of stochastic relaxation for simulating multivariate Gaussian measures are calculated and compared. Each sweep strategy prescribes a method for chosing which coordinates of the random vector are to be updated. Deterministic sweep strategies in which the coordinates are updated according to a fixed order are compared to random strategies in which the coordinate to be updated is chosen through some random mechanism. In addition block updating, in which a few coordinates are updated simultaneously, is compared to single coordinate updating.stochastic relaxation sweep strategies products of random affine maps rates of convergence