The nonlinear propagation of spark-generated N-waves through thermal turbulence is experimentally studied at the laboratory scale under well-controlled conditions. A grid of electrical resistors was used to generate the turbulent field, well described by a modified von Kármán model. A spark source was used to generate high-amplitude (~1500 Pa) and short duration (~50 μs) N-waves. Thousands of w...

The prediction distribution of generalized geometric series distribution (GGSD) and of its truncated and size-biased forms is derived and studied under the non-informative and beta prior distributions. The prediction distributions for all the models are beta distribution, but the parameters of the prediction distributions depend on the choice of the prior distribution as well as the model under...

In view of their importance and usefulness in reliability theory and probability distributions, several generalizations of the inverse Gaussian distribution and the Krätzel function are investigated in recent years. This has motivated the authors to introduce and study a new generalization of the inverse Gaussian distribution and the Krätzel function associated with a product of a Bessel functi...

Viewing the Matsumoto–Yor property as a bivariate property with respect to the simple tree with two vertices and one edge, we extend it to a p-variate property with respect to any tree with p vertices. The converse of the Matsumoto–Yor property, which characterizes the product of a gamma and a generalized inverse Gaussian distribution, is extended to characterize the product of a gamma and p 1 ...

There are three broad classes of models used to address the econometric problems caused by skewness in data commonly encountered in health care applications: (1) transformation to deal with skewness (e.g., OLS on ln(y)); (2) alternative weighting approaches based on exponential conditional models (ECM) and generalized linear model (GLM) approaches; and (3) survival models (Cox proportional haza...

This vignette describes the R hglm package via a series of applications that may be of interest to applied scientists. The hglm package implements the estimation algorithm for hierarchical generalized linear models. The package fits generalized linear models with random effects, where the random effect may come from a conjugate exponential-family distribution (Gaussian, Gamma, Beta or inverse-G...

Felsenstein's maximum-likelihood approach for inferring phylogeny from DNA sequences assumes that the rate of nucleotide substitution is constant over different nucleotide sites. This assumption is sometimes unrealistic, as has been revealed by analysis of real sequence data. In the present paper Felsenstein's method is extended to the case where substitution rates over sites are described by t...

We investigate the proximity in terms of zeta-structured metrics generalized negative binomial random sums to gamma distribution with corresponding parameters, extending thus estimates rate convergence Rényi theorem. In particular, we derive upper bounds for Kantorovich and Kolmogorov law large numbers i.i.d. variables nonzero first moments finite second moments. Our method is based on represen...

Abstract This vignette describes the R hglm package via a series of applications that may be of interest to applied scientists. The hglm package implements the estimation algorithm for hierarchical generalized linear models. The package fits generalized linear models with random effects, where the random effect may come from a conjugate exponential-family distribution (Gaussian, Gamma, Beta or ...

There are two broad classes of models used to address the econometric problems caused by skewness in data commonly encountered in health care applications: (1) transformation to deal with skewness (e.g., ordinary least square (OLS) on ln(y)); and (2) alternative weighting approaches based on exponential conditional models (ECM) and generalized linear model (GLM) approaches. In this paper, we en...