In this paper gaze shifts are considered as a realization of a stochastic process with non-local transition probabilities in a saliency field that represents a landscape upon which a constrained random walk is performed. The search is driven by a Langevin equation whose random term is generated by a Levy distribution, and by a Metropolis algorithm. Results of the simulations are compared with e...

A Bayesian Survival Analysis method is motivated and developed for analysing sequences of scores made by a batsman in test or first class cricket. In particular, we expect the presence of an effect whereby the distribution of scores has more probability near zero than a geometric distribution, due to the fact that batting is more difficult when the batsman is new at the crease. A Metropolis-Has...

We illustrate for 4D SU(2) and U(1) lattice gauge theory that sampling with a biased Metropolis scheme is essentially equivalent to using the heat bath algorithm. Only, the biased Metropolis method can also be applied when an efficient heat bath algorithm does not exist. For the examples discussed the biased Metropolis algorithm is also better suited for parallelization than the heat bath algor...

Consider the following method of card shuffling. Start with a deck of N cards numbered 1 through N . Fix a parameter p between 0 and 1. In this model a “shuffle” consists of uniformly selecting a pair of adjacent cards and then flipping a coin that is heads with probability p. If the coin comes up heads, then we arrange the two cards so that the lower-numbered card comes before the higher-numbe...

In this paper we consider spatial problems modeled by a Gaussian random field prior density and a nonlinear likelihood function linking the hidden variables to the observed data. We define a directional block Metropolis–Hastings algorithm to explore the posterior density. The method is applied to seismic data from the North Sea. Based on our results we believe it is important to assess the actu...

Randomization is an important technique for assessing the significance of data mining results. Given an input data set, a randomization method samples at random from some class of datasets that share certain characteristics with the original data. The measure of interest on the original data is then compared to the measure on the samples to assess its significance. For certain types of data, e....

In this paper, an attempt is made to show a general solution to nonlinear and/or non-Gaussian state space modeling in a Bayesian framework, which corresponds to an extension of Carlin, Polson and Stoffer (1992) and Carter and Kohn (1994, 1996). Using the Gibbs sampler and the Metropolis-Hastings algorithm, an asymptotically exact estimate of the smoothing mean is obtained from any nonlinear and...

One of the most widely used samplers in practice is the component-wise MetropolisHastings (CMH) sampler that updates in turn the components of a vector spaces Markov chain using accept-reject moves generated from a proposal distribution. When the target distribution of a Markov chain is irregularly shaped, a ‘good’ proposal distribution for one part of the state space might be a ‘poor’ one for ...

In this paper, we consider the problem of estimating stress-strength reliability for inverse Weibull lifetime models having the same shape parameters but different scale parameters. We obtain the maximum likelihood estimator and its asymptotic distribution. Since the classical estimator doesn’t hold explicit forms, we propose an approximate maximum likelihood estimator. The asymptotic confidenc...

We present counter-examples to demonstrate that when g is unbounded the conditions of Simultaneous Uniform Ergodicity and Diminishing Adaptation are not enough to guarantee that the the weak law of large numbers (WLLN) holds, although from the results of Roberts and Rosenthal [4] we know that WLLN holds under these conditions when g is bounded. Then we show various theoretical results of the WL...