Abstract The Fairlie-Gumbel-Morgenstern (FGM) family has been investigated in detail for various continuous marginals such as Cauchy, normal, exponential, gamma, Weibull, lognormal and others. It has been a popular model for the bivariate distribution with mild dependence. However, bivariate FGM’s with continuous marginals on a bounded support discussed in the literature are only those with uni...

A Taylor series approximation to multivariate integrals taken with respect to a multivariate probability distribution is proposed and applied to the computation of multivariate normal probabilities and conditional expectations. The approximation does not require that the multivariate distribution have a structured covariance matrix and, in its simplest form, can be written as the product of uni...

We argue that the distributions of both the intrinsic fluence and the intrinsic duration of the γ-ray emission in gamma-ray bursts from the BATSE sample are well represented by log-normal distributions, in which the intrinsic dispersion is much larger than the cosmological time dilatation and redshift effects. We perform separate bivariate log-normal distribution fits to the BATSE short and lon...

The bivariate Poisson distribution is a popular distribution for modeling bivariate count data. Its basic assumptions and marginal equi-dispersion, however, may prove limiting in some contexts. To allow for data dispersion, we develop here a bivariate Conway–Maxwell–Poisson (COM–Poisson) distribution that includes the bivariate Poisson, bivariate Bernoulli, and bivariate geometric distributions...

Meteorological stations usually contain some missing data for different reasons.There are several traditional methods for completing data, among them bivariate and multivariate linear and non-linear correlation analysis, double mass curve, ratio and difference methods, moving average and probability density functions are commonly used. In this paper a blended model comprising the bivariate expo...

A problem of estimating the location of a source of scattered radiation is considered. The role of extremes in estimation problems for truncated distributions is discussed from the Bayesian point of view. The emphasis is made on the bivariate case of spherically symmetric distributions. The cases of truncated normal, uniform, and Cauchy distributions are considered. Such location estimators as ...