Discriminant analysis for two data sets in IRd with probability densities f and g can be based on the estimation of the set G = {x : f(x) ≥ g(x)}. We consider applications where it is appropriate to assume that the region G has a smooth boundary. In particular, this assumption makes sense if...

Unobserved heterogeneity is a serious but often neglected problem in structural equation modelling (SEM) challenging the validity of many empirical results. Recently, a finite mixture approach to SEM has been proposed to resolve this problem but until now only a few studies analyse the...

Empirical applications of structural equation modeling (SEM) typically rest on the assumption that the analysed sample is homogenous with respect to the underlying structural model or that homogenous subsamples have been formed based on a priori knowledge. However, researchers often are ignorant...

The problem of selecting a clustering algorithm from the myriad of algorithms has been discussed in recent years. Many researchers have attacked this problem by using the concept of admissibility (e.g. Fisher and Van Ness, 1971, Yadohisa, et al., 1999). We propose a new criterion called the...

This paper discusses the admissibility of agglomerative hierarchical clustering algorithms with respect to space distortion and monotonicity, as defined by Yadohisa et al. and Batagelj, respectively. Several admissibilities and their properties are given for selecting a clustering algorithm....

As an explorative technique, duster analysis provides a description or a reduction in the dimension of the data. It classifies a set of observations into two or more mutually exclusive unknown groups based on combinations of many variables. Its aim is to construct groups in such a way that the...

We introduce a nonparametric smoothing procedure for nonparametric factor analaysis of multivariate time series. The asymptotic properties of the proposed procedures are derived. We present an application based on the residuals from the Fair macromodel. -- Factor Analysis ; Time Series ; Kernel...

We propose a nonparametric test for checking parametric hypotheses about the stationary density of weakly dependent observations. The test statistic is based on the L2-distance between a nonparametric and a smoothed version of a parametric estimate of the stationary density. It can be shown that...

Stochastic Volatility (SV) models are widely used in financial applications. To decide whether standard parametric restrictions are justified for a given dataset, a statistical test is required. In this paper, we develop such a test based on the linear state space representation. We provide a...

Let X be a continuous adapted process for which there exists an equivalent local martingale measure (ELMM). The minimal martingale measure P is the unique ELMM for X with the property that local P-martingales strongly orthogonal to the P-martingale part of X are also local P-martingales. We...