THE START AND EARLY HISTORY OF CHEMOMETRICS:SELECTED INTERVIEWS.PART 1

This is a first foray into the historical start and early years of chemometrics from about 1972 onwards.We have gathered interviews with three originators(Kowalski,Wold and Massart)as well as with aselected group of six other well-known chemometricians who gradually became active in the 1970s(Christie,Clementi,Hopke,Martens,Brown and Deming).The interviews include amongst a host ofsubjective recollections a succinct record of the key historical literature as highlighted by the interviewees'own rankings of‘earliest’and‘best’.A discussion of the most general commonalities in these interviews together with other historicalmaterial is presented in the second part of the paper.     

COMPARISON OF MEASUREMENT METHODS BASED ON A MODEL FOR THE ERROR STRUCTURE

Comparison of methods is a technique often used for investigation of systematic errors of measurementmethods.As concerns the design and analysis of such comparisons,much variety of opinion and practiceexists.In one approach a few specimens are measured several times by different operators in differentlaboratories(reproducibility conditions)and in another approach several specimens are measured on oneor a few occasions by one operator in the same laboratory(repeatability conditions).In this paper amodel for the error structure of measurements is formulated and it is emphasized that one has todistinguish between two types of systematic errors:the first type depends only on the level of themeasured quantity and the second type is specific for the separate specimens.On the basis of this modelthe information which can be obtained from the different designs of method comparisons is discussed.A new approach for the analysis of method comparisons with many specimens is also proposed.     

Evidence for Early LREE-enriched Mantle Source Regions: Diverse Magmas from the c. 3{middle dot}0 Ga Mallina Basin, Pilbara Craton, NW Australia

The c. 2·97–2·95 Ga magmatic history ofthe Mallina Basin, in the Pilbara Craton of NW Australia, includeswhat is perhaps the most lithologically diverse magmatism ofany similar-sized Archaean terrain, and is unusual for similar-sizedterrains of any age. The magmatism includes light rare earthelement (LREE)-rich basaltic rocks, LREE-rich gabbros and rockswith boninite-like compositions (collectively the ‘Mallinamafic suite’), and high-Mg diorites (sanukitoids). TheMallina mafic suite is characterized by high primitive mantlenormalized (La/Nb)_PM (>3) and (La/Yb)_PM (>2), and non-radiogenicNd-isotopic compositions (     

REGRESSION ON MULTIVARIATE IMAGES:PRINCIPAL COMPONENT REGRESSION FOR MODELING,PREDICTION AND VISUAL DIAGNOSTIC TOOLS

Regression between two blocks(usually called‘dependent’or Y and‘independent’or X)of data is a veryimportant scientific and data-analytical tool.Regression on multivariate images is possible and constitutesa meaningful addition to existing univariate and multivariate techniques of image analysis.The regressioncan be used as a modeling tool or for prediction.The form of the regression equation chosen is dependentupon problem specification and information at hand.This paper describes the use of principal componentregression(PCR).Both model building and prediction are presented for continuous Y-variables.The finalgoal is to supply new image material that can be used for visual inspection on a screen.Also,visual toolsfor diagnosis of model and prediction are provided,often based on derived image material.Examplesof modeling and prediction are given for six channels in a seven-channel satellite image     

CAN IMAGE ANALYSIS PROVIDE INFORMATION USEFUL IN CTTEMISTRY?

Images can contain chemical information and many chemical methods can generate image data. For anefficient extraction of chemical data from images, data analysis techniques are necessary, It is a greatadvantage to be able to work on multivariate images. Many imaging techniques allow the extraction ofchemical information. Inorganic analytical chemistry seems to have the longest tradition here, butorganic chemistry and biochemistry may soon be catching up. Also large data arrays from non-imagingtechniques can be combined with image analysis in a useful way, provided certain conditions are fulfilled.