A weighted multivariate signed-rank test is introduced for an analysis of multivariate clustered data. Observations in different clusters may then get different weights. The test provides a robust and efficient alternative to normal theory based methods. Asymptotic theory is developed to find...

The so-called independent component (IC) model states that the observed p-vectorX is generated via X=[Lambda]Z+[mu], where [mu] is a p-vector, [Lambda] is a full-rank matrix, and the centered random vector Z has independent marginals. We consider the problem of testing the null hypothesis on the...

Clustered data arise commonly in practice and it is often of interest to estimate the mean response parameters as well as the association parameters. However, most research has been directed to address the mean response parameters with the association parameters relegated to a nuisance role....

The speech mainly gives insights into aspects like what is globalisation, urban growth in the next 30 years, new challenges of Globalisation for Cities, the poor that emerges along with the cities, the demographic changes that are going to take place, urban financing and governance [Plenary...

In this paper a numerical method to compute principal component geodesics for Kendall's planar shape spaces-which are essentially complex projective spaces-is presented. Underlying is the notion of principal component analysis based on geodesics for non-Euclidean manifolds as proposed in an...

The penalized profile sampler for semiparametric inference is an extension of the profile sampler method [B.L. Lee, M.R. Kosorok, J.P. Fine, The profile sampler, Journal of the American Statistical Association 100 (2005) 960-969] obtained by profiling a penalized log-likelihood. The idea is to...

A nearly unstable sequence of stationary spatial autoregressive processes is investigated, when the sum of the absolute values of the autoregressive coefficients tends to one. It is shown that after an appropriate normalization the least squares estimator for these coefficients has a normal...

In this paper, we define two restricted estimators for the regression parameters in a multiple linear regression model with measurement errors when prior information for the parameters is available. We then construct two sets of improved estimators which include the preliminary test estimator,...