This paper is concerned with the online public engagement ‘Leitbild Metropolis Hamburg – Growing City’ which has been conducted in the context of the EU project DEMOS (Delphi Mediation Online System). The result of DEMOS is an innovative Internet platform facilitating democratic discussions and participative public opinion formation. The test of the DEMOS approach and the software system during...

In this paper we propose a simple adaptive Metropolis-within-Gibbs algorithm attempting to study directions on which the Metropolis algorithm can be ran flexibly. The algorithm avoids the wasting moves in wrong directions by proposals from the full dimensional adaptive Metropolis algorithm. We also prove its ergodicity, and test it on a Gaussian Needle example and a real-life Case-Cohort study ...

In this paper we shall consider optimal scaling problems for highdimensional Metropolis–Hastings algorithms where updates can be chosen to be lower dimensional than the target density itself. We find that the optimal scaling rule for the Metropolis algorithm, which tunes the overall algorithm acceptance rate to be 0.234, holds for the so-called Metropolis-within-Gibbs algorithm as well. Further...

The Hastings-Metropolis algorithm is a general MCMC method for sampling from a density known up to a constant. Geometric convergence of this algorithm has been proved under conditions relative to the instrumental distribution (or proposal). We present an inhomogeneous Hastings-Metropolis algorithm for which the proposal density approximates the target density, as the number of iterations increa...

We describe a serial algorithm called feature-inclusion stochastic search, or FINCS, that uses online estimates of edge-inclusion probabilities to inform the process of Bayesian model determination in Gaussian graphical models. FINCS is compared to Metropolis-based search methods and found to be superior along a variety of dimensions, leading to more accurate and less volatile estimates of edge...

We discuss several methods that improve the partial-global stochastic Metropolis (PGSM) algorithm for smeared link staggered fermions. We present autocorrelation time measurements and argue that this update is feasible even on reasonably large lattices. Smeared link actions have gained popularity in recent years. These actions have many desirable features: improved flavor symmetry with staggere...

This paper examines the constraints to physical planning in Kano Metropolis. Kano been one of the most populous cities in Nigeria, is undergoing tremendous urban expansion particularly at the edge of the city. This expansion could be attributed to not only population growth but also redistribution of activities within the metropolitan area. Rapid population growth has increased the tendency of ...

that is, the sample covariance matrix of the history of the chain plus a (small) constant ǫ > 0 multiple of the identity matrix I. The lower bound on the eigenvalues of Sn induced by the factor ǫI is theoretically convenient, but practically cumbersome, as a good value for the parameter ǫ may not always be easy to choose. This article considers variants of the AM algorithm that do not explicitl...

This paper investigates Bayesian estimation for Gaussian Markov random elds. In particular, a new class of inhomogeneous model is proposed. This inhomogeneous model uses a Markov random eld to describe spatial variation of the smoothing parameter in a second random eld which describes the spatial variation in the observed intensity image. The coupled Markov random elds will be used as prior dis...

Abstract Under a compactness assumption, we show that a φ-irreducible and aperiodic MetropolisHastings chain is geometrically ergodic if and only if its rejection probability is bounded away from unity. In the particular case of the Independence Metropolis-Hastings algorithm, we obtain that the whole spectrum of the induced operator is contained in (and in many cases equal to) the essential ran...