Accurately quantifying animals' spatial utilisation is critical for conservation, but has long remained an elusive goal due to technological impediments. The Argos telemetry system has been extensively used to remotely track marine animals, however location estimates are characterised by substantial spatial error. State-space models (SSM) constitute a robust statistical approach to refine Argos...

Knowledge concerning the family of univariate continuous distributions with density function f and distribution function F defined through the relation f(x) = F (x)(1 − F (x)), α, β ∈ R, is reviewed and modestly extended. Symmetry, modality, tail behaviour, order statistics, shape properties based on the mode, L-moments and — for the first time — transformations between members of the family ar...

We consider statistical models which have been proposed for luminosity distributions for the globular clusters in the Milky Way and M31. Although earlier research showed that the cluster luminosity functions in those two galaxies were well fit by Gaussian distributions, subsequent investigations suggested that their luminosities were better fit by t-, rather than Gaussian, distributions. By app...

This article provides a fully bayesian approach for modeling of single-dose and complete pharmacokinetic data in a population pharmacokinetic (PK) model. To overcome the impact of outliers and the difficulty of computation, a generalized linear model is chosen with the hypothesis that the errors follow a multivariate Student t distribution which is a heavy-tailed distribution. The aim of this s...

A stochastic volatility-in-mean model with correlated errors using the generalized hyperbolic skew Student-t (GHST) distribution provides a robust alternative to the parameter estimation for daily stock returns in the absence of normality. An efficient Markov chain Monte Carlo (MCMC) sampling algorithm is developed for parameter estimation. The deviance information, the Bayesian predictive info...

This article deals with the estimation of the parameters of an α-stable distribution by the indirect inference method with the skewed-t distribution as an auxiliary model. The latter distribution appears as a good candidate for an auxiliary model since it has the same number of parameters as the α-stable distribution, with each parameter playing a similar role. To improve the properties of the ...

This paper deals with Student t-processes as studied in (Cufaro Petroni 2007). We prove and extend some conjectures expressed by Cufaro Petroni about the asymptotical behavior of a Student t-process and the expansion of its density. First, the explicit asymptotic behavior of any real positive convolution power of a Student t-density with any real positive degrees of freedom is given in the mult...

Small area estimation using linear area level models typically assumes normality of the area level random effects (model errors) and of the survey errors of the direct survey estimates. Outlying observations can be a concern, and can arise from outliers in either the model errors or the survey errors, two possibilities with very different implications. We consider both possibilities here and in...

coincides with the standard (central) tν distribution. In the following, represents the effect size; by convention, a of 0.5 is considered a "medium" effect size. In Figure 1 are shown three instances of the t′ density envelope for ν = 10, one with δ = 0 (a standard t), and two with δ = 3 and δ = 6 : one may note that, whereas t10(δ = 0) is centered at 0 and symmetrical, the non-central t′’s ar...

Often a structural model implies that certain moment functions expressed in terms of data and model parameters follow a distribution. An assertion that moment functions follow a distribution logically implies a distribution on the arguments of the moment functions. This fact would appear to permit Bayesian inference on model parameters. The classic example is an assertion that the sample mean c...