The method of moments is an old statistical technique that fits parameters of a model by matching the average value of moments under the model with their average value over the data. Recently, approximate versions of this basic technique have been proposed in several diverse literatures including statistics, econometrics, population genetics, systems biology, ecology, epidemiology, and image te...

BACKGROUND In the absence of stochasticity, allometric growth throughout ontogeny is axiomatically described by the logarithm-transformed power-law model, θt = log(a) b + kφ(t), where θt ≡ θ(t) and φt ≡ φ(t) are the logarithmic sizes of two traits at any given time t. Realistically, however, stochasticity is an inherent property of ontogenetic allometry. Due to the inherent stochasticity in bot...

Introduction: A major problem facing the patients with chronic liver diseases is the diagnostic procedure.  The conventional diagnostic method depends mainly on needle biopsy which is an invasive method. There  are  some  approaches  to  develop  a  reliable  noninvasive  method  of  evaluating  histological  changes  in  sonograms. The main characteristic used to distinguish between the normal...

We introduce a new micro-macro decomposition of collisional kinetic equations in the specific case of the diffusion limit, which naturally incorporates the incoming boundary conditions. The idea is to write the distribution function f in all its domain as the sum of an equilibrium adapted to the boundary (which is not the usual equilibrium associated with f) and a remaining kinetic part. This e...

Finding time separation of events is a fundamental problem in the analysis of asynchronous systems. When component delays have statistical variations, it is both interesting and useful to compute moments of time separation of events. Traditionally, Monte Carlo simulation has been used for this purpose. However, Monte Carlo simulation requires knowledge of the probability distributions of compon...

In this paper we propose a new statistical model for multi-scale traffic, and present an exact queueing analysis for the model. The model is based on the central moments and the marginal distributions of the cumulative traffic loads in different time scales. Only the first two moments are needed to characterize the traffic process, which greatly simplifies the representation and estimation. The...

This paper presents a dimensional decomposition method for obtaining probabilistic descriptors of realvalued eigenvalues of positive semi-definite random matrices. The method involves a novel function decomposition allowing lower-variate approximations of eigenvalues, lower-dimensional numerical integration for statistical moments, and Lagrange interpolation facilitating efficient Monte Carlo s...

Shanker [3] obtained a PoissonAkash distribution (PAD), a Poisson mixture of Akash distribution, and discussed its various statistical and mathematical properties along with estimation of parameter and applications for count data from different fields of knowledge. Shanker [4,5] has also introduced size-biased and zero-truncated version of PAD and studied their properties, estimation of paramet...

The impact of the third (skewness) and fourth (kurtosis) reduced centered moments on the statistical modeling of E1 lines in complex atomic spectra is investigated through the use of Gram-Charlier, Normal Inverse Gaussian and Generalized Gaussian distributions. It is shown that the modeling of unresolved transition arrays with nonGaussian distributions may reveal more detailed structures, due e...

We present numerical and analytical results for a stochastic representation of immiscible flow in a heterogeneous reservoir. Using a perturbation method, we derive equations of statistical moments to second order in the standard deviation of log permeability. We allow these moments to depend on location, hence the common assumption of statistical homogeneity (stationarity) does not apply. This ...