The Minimum Covariance Determinant (MCD) estimator is a highly robust procedure for estimating the centre and shape of a high dimensional data set. It consists of determining a subsample of h points out of n which minimises the generalised variance. By definition, the computation of this...

Recently (Beh, 2008, JSPI) presented an index that helps to identify how likely two dichotomous categorical variables may be associated given only the aggregate (or marginal) information. Such an index was referred to as the aggregate association index. This paper will further consider some...

Fusion of information from graph features and content can provide superior inference for an anomaly detection task, compared to the corresponding content-only or graph feature-only statistics. In this paper, we design and execute an experiment on a time series of attributed graphs extracted from...

To compare two treatment effects, which can be described as the difference of the parameters in two linear models, we propose an empirical likelihood-based method to make inference for the difference. Our method is free of the assumptions of normally distributed and homogeneous errors, and equal...

Simultaneous confidence intervals are used in Scheffé (1953) to assess any contrasts of several normal means. In this paper, the problem of assessing any contrasts of several simple linear regression models by using simultaneous confidence bands is considered. Using numerical integration,...

We obtain designs which are optimally robust against possibly misspecified regression models, assuming that the parameters are to be estimated by one of several types of M-estimation. Such designs minimize the maximum mean squared error of the predicted values, with the maximum taken over a...

Linear regression models for de facto exchange rate regime classification are complemented by inferential techniques for evaluating the stability of the regimes. To simultaneously assess parameter instabilities in the regression coefficients and the error variance an (approximately) normal...

In interval-censored survival data, the event of interest is not observed exactly but is only known to occur within some time interval. Such data appear very frequently. In this paper, we are concerned only with parametric forms, and so a location-scale regression model based on the...

A new technique based on Bayesian quantile regression that models the dependence of a quantile of one variable on the values of another using a natural cubic spline is presented. Inference is based on the posterior density of the spline and an associated smoothing parameter and is performed by...

A modified active subset selection method based on quadratic Rényi entropy and a fast cross-validation for fixed-size least squares support vector machines is proposed for classification and regression with optimized tuning process. The kernel bandwidth of the entropy based selection criterion...