Recently, a generalization of the Pearson differential equation has appeared in the literature, from which a vast majority of continuous probability density functions (pdf’s) can be generated, known as the generalized Pearson system of continuous probability distributions. This paper derives a new family of distributions based on the generalized Pearson differential equation, which is a natural...

This paper discusses two classes of distributions, and stochastic processes derived from them: modified stable (MS) laws and normal modified stable (NMS) laws. This extends corresponding results for the generalised inverse Gaussian (GIG) and generalised hyperbolic (GH) or normal generalised inverse Gaussian (NGIG) laws. The wider framework thus established provides, in particular, for added fle...

Gaussian assumptions of non-Gaussian noises hinder the improvement state estimation accuracy. In this paper, an asymmetric generalized distribution (AGGD), as a unified representation various unimodal distributions, is applied to formulate forecasting-aided problem. To address problem, novel particle filter method proposed, which integrates near-optimal AGGD proposal function and sampling into ...

The mixture of inverse covariances model is a low-complexity, approximate decomposition of the inverse covariance matrices in a Gaussian mixture model which achieves high modeling accuracy with very good computational efficiency. In this model, the inverse covariances are decomposed into a linear combination of K shared prototype matrices. In this paper, we introduce an extension of this model ...

We present a nonparametric Bayesian hierarchical (NBH) model and develop variational approximation (VA) algorithm for the curve fitting of functional radiation response data. The NBH is based on (BH) with Gaussian-Inverse Wishart process (G-IWP) prior, which simultaneously smooths multiple observations estimates mean-covariance functions. use automatic differentiation inference (ADVI) Gaussian ...

Measurement of the T2 distribution in tissues provides biologically relevant information about normal and abnormal microstructure and organization. Typically, the T2 distribution is obtained by fitting the magnitude MR images acquired by a multi-echo MRI pulse sequence using an inverse Laplace transform (ILT) algorithm. It is well known that the ideal magnitude MR signal follows a Rician distri...

Measurement of the T2 distribution in tissues provides biologically relevant information about normal and abnormal microstructure and organization. Typically, the T2 distribution is obtained by fitting the magnitude MR images acquired by a multi-echo MRI pulse sequence using an inverse Laplace transform (ILT) algorithm. It is well known that the ideal magnitude MR signal follows a Rician distri...

In a previous paper [Bag and Hu, Phys. Rev. E 73, 061107 (2006)], we studied the mean lifetime (MLT) for the escape of a Brownian particle through an unstable limit cycle driven by multiplicative colored Gaussian and additive Gaussian white noises and found resonant activation (RA) behavior. In the present paper we switch from Gaussian to non-Gaussian multiplicative colored noise. We find that ...