The random walk Metropolis algorithm is a simple Markov chain Monte Carlo scheme which is frequently used in Bayesian statistical problems. We propose a guided walk Metropolis algorithm which suppresses some of the random walk behavior in the Markov chain. This alternative algorithm is no harder to implement than the random walk Metropolis algorithm, but empirical studies show that it performs ...

Healthcare-associated infections are of different forms, with Surgical Site Infections (SSI) being the second most common type, they continue to be a relatively postoperative complications and frequent reason for re-admission following surgery. Several data from around world revealed Staphylococcus aureus leading cause surgical site infection. Therefore, this study aimed determine occurrence dr...

For SU(2) lattice gauge theory with the fundamental-adjoint action an efficient heat-bath algorithm is not known so that one had to rely on Metropolis simulations supplemented by overrelaxation. Implementing a novel biased Metropolis-heat-bath algorithm for this model, we find improvement factors in the range 1.45 to 2.06 over conventionally optimized Metropolis simulations. If one optimizes fu...

A hybrid algorithm is proposed for pure SU(N) lattice gauge theory based on Genetic Algorithms (GA)s and the Metropolis method. We apply the hybrid GA to pure SU(2) gauge theory on a 2-dimensional lattice and find the action per plaquette and Wilson loops being consistent with those given by the Metropolis and Heatbath methods. The thermalization of this newly proposed Hybrid GA is quite faster...

The waste-recycling Monte Carlo (WRMC) algorithm introduced by physicists is a modification of the (multi-proposal) Metropolis–Hastings algorithm, which makes use of all the proposals in the empirical mean, whereas the standard (multi-proposal) Metropolis–Hastings algorithm uses only the accepted proposals. In this paper we extend the WRMC algorithm to a general control variate technique and ex...

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introduction: increase of environmental challenges inevitably changes our methods; challenges such as rapid change, diversity of workforce, globalization, evolution and transformation of business and family roles, lack of skills and emergence of service sector affect not only the organizational structure but also the nature and functional role of business. in response to these environmental cha...

The Metropolis process is an extremely general recipe for constructing a Markov chain which has any desired stationary distribution π on a finite set Ω. Moreover, this distribution can be specified just by a weight function w : Ω → R, so that π(x) = w(x) Z where Z is an unknown normalizing factor. The Metropolis process is named after one of its inventors [MR+53]. To specify the Metropolis proc...

The waste-recycling Monte Carlo (WR) algorithm introduced by physicists is a modification of the (multi-proposal) Metropolis-Hastings algorithm, which makes use of all the proposals in the empirical mean, whereas the standard (multi-proposal) Metropolis-Hastings algorithm only uses the accepted proposals. In this paper, we extend the WR algorithm into a general control variate technique and exh...

When a graph can be decomposed into clusters of well connected subgraphs, it is possible to speed up random walks taking advantage of the topology of the graph. In this work, a new random walk scheme is introduced and a condition is given when the new random walk performs better than the Metropolis algorithm.