Graphical Tools for the Detection of Multiple Outliers in Spatial Statistics Models

Cerioli and Riani (1998) recently suggested a novel approach to the exploratory analysis of spatially autocorrelated data, which is based on a forward search. In this paper we suggest a modification of the original technique, namely a block-wise forward search algorithm. Furthermore, we show the effectiveness of our approach in two examples which may be claimed to be ‘difficult’ to analyse in practice. In this respect we also show that our method can provide useful guidance to the identification of nonstationary trends over the observation area. Throughout, the emphasis is on exploratory methods and joint display of cogent graphical plots for the visualization of relevant spatial features of the data.