The bivariate Sinh-Elliptical (BSE) distribution is a generalization of the well-known Rieck’s (1989) Sinh-Normal distribution that is quite useful in Birnbaum–Saunders (BS) regression model. The main aim of this paper is to define the BSE distribution and discuss some of its properties,...

Separation of the linear and nonlinear components in additive models based on penalized likelihood has received attention recently. However, it remains unknown whether consistent separation is possible in generalized additive models, and how high dimensionality is allowed. In this article, we...

When the likelihood functions are either unavailable analytically or are computationally cumbersome to evaluate, it is impossible to implement conventional Bayesian model choice methods. Instead, approximate Bayesian computation (ABC) or the likelihood-free method can be used in order to avoid...

Selection criteria and misspecification tests for the intra-cluster correlation structure (ICS) in longitudinal data analysis are considered. In particular, the asymptotical distribution of the correlation information criterion (CIC) is derived and a new method for selecting a working ICS is...

Risk difference is an important measure of effect size in biostatistics, for both randomised and observational studies. The natural way to adjust risk differences for potential confounders is to use an additive binomial model, which is a binomial generalised linear model with an identity link...

Estimation of a covariance matrix or its inverse plays a central role in many statistical methods. For these methods to work reliably, estimated matrices must not only be invertible but also well-conditioned. The current paper introduces a novel prior to ensure a well-conditioned maximum a...

Bounding probabilities of rare events in the context of computer experiments is an important concern in reliability studies. These rare events depend on the output of a physical model with random input variables. Since the model is only known through an expensive black box function, standard...

Variable selection has been suggested for Random Forests to improve data prediction and interpretation. However, the basic element, i.e. variable importance measures, cannot be computed straightforward when there are missing values in the predictor variables. Possible solutions are multiple...

Under a random effects logistic regression model, asymptotic and exact test procedures in closed form for testing equality of binary responses are developed for comparing three treatments in a three-period crossover trial. Monte Carlo simulation is employed to evaluate the performance of these...

The robust estimation for Poisson autoregressive models is studied. As a robust estimator, a minimum density power divergence estimator (MDPDE) is considered. It is shown that under regularity conditions, the MDPDE is strongly consistent and asymptotically normal. Simulation results are provided...