Relationships between sets of variables of different kinds are of interest in many branches of
science. The question of the analysis of relationships of this sort has nevertheless rather …

Palaeoecologists and palaeobiogeographers are often confronted with large, multivariate
data sets, from which fossil communities (assemblages or associations) or faunal provinces …

Abstract In Chapter 3, Section 3.6 we introduced the basic theory for estimating the
nonrandom, fixed parameter matrix B qxp for the multivariate (linear) regression (MR) model …

The Wiley-Interscience Paperback Series consists of selected books that have been made
more accessible to consumers in an effort to increase global appeal and general circulation …

The concern over outliers is old and undoubtedly dates back to the first attempt to base
conclusions on a set of statistical data. Comments by Bernoulli (1777) indicate that the …

In this work, we focus on the use of influence functions to identify relevant training examples
that one might hope “explain” the predictions of a machine learning model. One shortcoming …

Recently many scientific and engineering applications have involved the challenging task of
analyzing large amounts of unsorted high-dimensional data that have very complicated …

In this paper, we compare some traditional statistical methods for predicting financial
distress to some more “unconventional” methods, such as decision tree classification, neural …

Lake Cajititlán is a shallow body of water located in an endorheic basin in western Mexico.
This lake receives excess fertilizer runoff from agriculture and approximately 2.3 Hm 3 per …

In linear regression, the theoretical influence function and the various sample versions of it
have an established place as diagnostic tools. These same functions are developed here to …