The Gibbs sampler, Metropolis’ algorithm, and similar iterative simulation methods are related to rejection sampling and importance sampling, two methods which have been traditionally thought of as non-iterative. We explore connections between importance sampling, iterative simulation, and importance-weighted resampling (SIR), and present new algorithms that combine aspects of importance sampli...

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...

Assessing the relationship between spawning sto k size and the resulting number of adult o spring (re ruitment) is one of the most fundamental issues in sheries sto k assessment and an important ornerstone for management de isions on harvest poli ies in many sheries. This paper proposes a Bayesian state-spa e model for tting sto kre ruitment urves. This approa h eliminates at least two of the f...

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 ...

Composite likelihoods are increasingly used in applications where the full likelihood is analytically unknown or computationally prohibitive. Although some frequentist properties of the maximum composite likelihood estimator are akin to those of the maximum likelihood estimator, Bayesian inference based on composite likelihoods is in its early stages. This paper discusses inference when one use...

Step 1: τ 2 The components of τ 2 can be sampled independently with only the corresponding element of η affecting the sampling. For efficiency of the implementation, only τ j for j with γj = 1 are actually sampled in this step as the others do not affect the linear model. For others, the full conditional distribution is the prior and sampling is done just-in-time, if they are considered for add...

Recently, there has been a great deal of research focusing on the development of sampling algorithms for networks with small-world and/or power-law structure. The peerto-peer research community (e.g., [7]) have used sampling to quickly explore and obtain a good representative sample of the network topology, as these networks are hard to explore completely and have significant amounts of churn i...

We propose a new non-parametric algorithm that can be implemented to study and characterize stellar clusters. The scheme attempts to simultaneously recover the stellar distribution function and the cluster potential by using projected radii and velocity information about the cluster members. The pair of these functions that is most consistent with the input data is detected by the Metropolis al...

We consider Bayesian image segmentation from a continuum parametric model. This is a class of problems in which a great deal of prior information is generally available. This information is often hierarchical in character, concerning the appearance of a range of different types of composite structures, including edges, vertices, regions, and the topology of the boundary graphs. Bayesian inferen...