As Bayesian networks are applied to more complex and realistic real-world applications, the development of more efficient inference approaches is increasingly important. This paper presents a method for metareasoning in Bayesian networks adopting prediction models to select algorithms for the inference tasks, when multiple schemes are used to calculate the propagation of evidence. The proposed ...

In almost all random sampling schemes, we adopt different sampling designs with an objective of obtaining a better representative sample (optimal sample) for the population. Application of different randomization techniques were adopted for providing a supportive basis for this. Now the question arises, whether the final sample selected, on which all our efforts are utilized, from the populatio...

This paper presents some results on semi-parametric regression using wavelet methods in the presence of autocorrelated stationary Gaussian errors, and when the explanatory variable follows an Uniform distribution. It is shown that this Uniform distribution arrives in the special cases of stochastic sampling: the Poisson and the jittered sampling schemes. The aim is to estimate the signal global...

AbstructWe investigate a very general subset of 2-D, orthogonal, compactly supported wavelets. This subset includes all the wavelets with a corresponding wavelet (polyphase) matrix that can be factored as a product of factors of degree-1 in one variable. In this paper, we consider, in particular, wavelets with vanishing moments. The number of vanishing moments that can be aichieved increases wi...

We investigate a very general subset of two-dimensional, orthogonal, compactly supported wavelets. This subset includes all the wavelets with a corresponding wavelet (polyphase) matrix that can be factored as a product of factors of degree-1 in one variable. In this paper we consider in particular wavelets with vanishing moments. The number of vanishing moments that can be achieved increases wi...

We consider the exact path sampling of the squared Bessel process and some other continuous-time Markov processes, such as the CIR model, constant elasticity of variance diffusion model, and hypergeometric diffusions, which can all be obtained from a squared Bessel process by using a change of variable, time and scale transformation, and/or change of measure. All these diffusions are broadly us...

Deliberate nonuniform sampling promises increased equivalent sampling rates with reduced overall hardware costs of the DSP system. The equivalent sampling rate is the sampling rate that a uniform sampling device would require in order to achieve the same processing bandwidth. Equivalent bandwidths of realizable systems may well extend into the GHz range while the mean sampling rate stays in the...

The paper presents a method for generating solutions of a constraint satisfaction problem (CSP) uniformly at random. Our method relies on expressing the constraint network as a uniform probability distribution over its solutions and then sampling from the distribution using state-of-the-art probabilistic sampling schemes. To speed up the rate at which random solutions are generated, we augment ...

The numbers of greenbugs, Schizaphis graminum (Rondani), and bird cherry-oat aphids, Rhopalosiphum padi L., per wheat tiller (stem) were estimated in 189 production winter wheat (Triticum aestivum L.) fields located throughout Oklahoma. Taylor's power law regressions were calculated from these data and used to construct fixed precision sequential sampling schemes for each species. An evaluation...

In this paper we focus on the test selection problem. It is modeled after a real-life problem that arises in telecommunication when one has to check the reliability of an application. We apply different metaheuristics, namely Reactive Tabu Search (RTS), Genetic Algorithms (GA) and Simulated Annealing (SA) to solve the problem. We propose some modifications to the conventional schemes including ...