In geostatistics, spatial data will be analysed that often come from irregularly distributed sampling locations. Interest is in modelling the data, i.e. estimating distributional parameters and then to predict the phenomenon under study at unobserved sites within the corresponding sampling...

Numerous methods have been proposed for dealing with the serious practical problems associated with the conventional analysis of covariance method, with an emphasis on comparing two groups when there is a single covariate. Recently, Wilcox (2005a: section 11.8.2) outlined a method for handling...

Many methods have been developed for detecting multiple outliers in a single multivariate sample, but very few for the case where there may be groups in the data. We propose a method of simultaneously determining groups (as in cluster analysis) and detecting outliers, which are points that are...

This paper extends the forward search technique to the analysis of structural time series data. It provides a series of powerful new forward plots that use information from the whole sample to display the effect of each observation on a wide variety of aspects of the fitted model and shows how...

We consider the problem of extraction of trend and chaotic components from irregular stock market time series. The proposed methods also permit to extract a part of chaotic component, the so-called anomalous term, caused by the transient short-time surges with high amplitudes. This provides more...

This paper extends the forward search technique to the analysis of structural time series data. It provides a series of powerful new forward plots that use information from the whole sample to display the effect of each observation on a wide variety of aspects of the fitted model and shows how...