A proper choice of a proposal distribution for MCMC methods, e.g. for the Metropolis-Hastings algorithm, is well known to be a crucial factor for the convergence of the algorithm. In this paper we introduce an adaptive Metropolis Algorithm (AM), where the Gaussian proposal distribution is updated along the process using the full information cumulated so far. Due to the adaptive nature of the pr...

A proper choice of a proposal distribution for Markov chain Monte Carlo methods, for example for the Metropolis±Hastings algorithm, is well known to be a crucial factor for the convergence of the algorithm. In this paper we introduce an adaptive Metropolis (AM) algorithm, where the Gaussian proposal distribution is updated along the process using the full information cumulated so far. Due to th...

W orld Environment Day 2005 might be just the moment to highlight some pristine location that showcases what we most value about our environment: clean air, pure water, uncluttered landscapes, and rich plant and animal life. But instead, the United Nations (UN) Environment Programme turns to a city, San Francisco, as the focus for its celebrations. The reason is simple: Cities are where people ...

Electronic system design has been becoming more and more complex. It is very common to have dozens of IP modules in a single system. To quickly simulate the system is becoming a challenge. On the other hand, computing facilities, on which people run actual simulation, are becoming more and more powerful by having more powerful single processor and by building parallel machines. However, there i...

A Kernel Adaptive Metropolis-Hastings algorithm is introduced, for the purpose of sampling from a target distribution with strongly nonlinear support. The algorithm embeds the trajectory of the Markov chain into a reproducing kernel Hilbert space (RKHS), such that the feature space covariance of the samples informs the choice of proposal. The procedure is computationally efficient and straightf...

The study examined the effect of internet banking on small and medium enterprises performance in Enugu Metropolis. Specifically this aims to determine (i) effectiveness business expansion Metropolis, (ii) convenience enterprise quality job delivery made use descriptive survey design. used structured questionnaire obtain data. population is 650 with sample size 264. Summary includes: findings re...

The field is expanded in a wavelet series and the wavelet coefficients are varied in a simulation of the 2D φ 4 field theory. The drastically reduced autocorrelations result in a substantial decrease of computing requirements, compared to those in local Metropolis simulations. The improvement is shown to be the result of an additional freedom in the choice of the allowed range of change at the ...

We present Metropolis Instant Radiosity (MIR), an unbiased algorithm to solve the Light Transport problem. MIR is a hybrid technique which consists in representing the incoming radiance field by a set of Virtual Point Lights (VPLs) and in computing the response of all sensors in the scene (i.e. camera captors) by accumulating their contributions. In contrast to other similar approaches, we prop...

| This paper presents a geometric approach to estimating subspaces as elements of complex Grassmann-manifold, with each subspace represented by its unique, complex projection matrix. Variation between the sub-spaces is modeled by rotating their projection matrices via the action of unitary matrices (elements of the unitary group (U(n))). Subspace estimation or tracking then corresponds to the i...

The Metropolis algorithm [8] is a mainstay of scientific computing. Indeed it appears first on a list of the “Top Ten Algorithms” [12]. It gives a method for sampling from probability distributions on high-dimensional spaces when these distributions are only known up to a normalizing constant. For background and references to extensive applications in physics, chemistry, biology and statistics,...