Statistical abduction is an attempt to define a probability distribution over explanations derived by abduction and to evaluate them using their probabilities. In statistical abduction, deterministic knowledge like rules and facts are described as logic formulas. However nondeterministic knowledge like preference and frequency seems difficult to represent as logic. Bayesian inference can reflec...

In automatic surface inspection, one has to solve the problem of detecting small surface defects which locally break the homogeneity of a texture pattern. Textures are generally classified into two major types, structural and statistical [1]. Structural textures are those that are composed of repetitions of some basic texture primitive, such as directional lines, with a deterministic rule of di...

Submit Manuscript | http://medcraveonline.com on PTEs and Stein-type estimators for various linear models. In statistical inference, the use of prior information on other parameters in a statistical model, usually leads to improved inference on the parameter of interest. Prior information may he (i) known and deterministic which is then incorporated into the model in the form of constraints on ...

We prove that all deterministic hidden-variables theories, that reproduce quantum theory for an ‘equilibrium’ distribution of hidden variables, give instantaneous signals at the statistical level for hypothetical ‘nonequilibrium ensembles’. This generalises another property of de Broglie-Bohm theory. Assuming a certain symmetry, we derive a lower bound on the (equilibrium) fraction of outcomes ...

Recurrence quantification analysis is a nonlinear time series analysis technique that detects deterministic dependencies in time series. This technique is particularly appropriate for modeling financial time series since it requires no assumptions on stationarity, statistical distribution, and minimum number of observations. This chapter illustrates two applications of recurrence quantification...

The effect of direct processes on the statistical properties of deterministic scattering processes in a chaotic waveguide is examined. The single-channel Poisson kernel describes well the distribution of S-matrix eigenphases when evaluated over an energy interval. When direct processes are transformed away, the scattering processes exhibit universal random matrix behavior. The effect of chaos o...

We propose a Bayesian approach to joint source separation and restoration for astrophysical diffuse sources. We constitute a prior statistical model for the source images by using their gradient maps. We assume a t-distribution for the gradient maps in different directions, because it is able to fit both smooth and sparse data. A Monte Carlo technique, called Langevin sampler, is used to estima...

Two types of electrocardiographic data series were investigated using appropriate tests based on a selection of semi-quantitative analysis algorithms. Distribution histograms, power spectra, auto-correlation functions, state-space portraits, Lyapunov exponents and wavelet transformations were applied to electrocardiograms of normal and stressed subjects. Statistical analysis using the Student's...