Comparing sweep strategies for stochastic relaxation

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

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