Topics of Chemometrics Today

An historical overview of chemometrics is presented, and the role of chemometric techniques in analytical chemistry, statistics, organic, physical and environmental chemistry and computer science evaluated. The interaction between statistics and other disciplines, including environmental chemistry, is described. The main textbooks and meetings are listed. Considerable emphasis is placed on software. The type of software used depends on the expertise and experience of the user ranging from statistical macrolanguages to microprocessor based packaged software, instrumental software and home grown programs using a variety of languages and, also, object oriented techniques. An extensive bibliography is presented.

[1]  G Blomquist,et al.  Classification of fungi by means of pyrolysis-gas chromatography-pattern recognition. , 1979, Journal of Chromatography A.

[2]  Eric Huggins.  Mastering Pascal Programming , 1983 .

[3]  Bruce R. Kowalski,et al.  Chemometrics: Theory and Application , 1977 .

[4]  N. B. Vogt,et al.  Composition activity relationships — CARE: Part II. Indirect and direct mutagens multivariate dose-response regression , 1989 .

[5]  Thomas L. Isenhour,et al.  Chemical applications of pattern recognition , 1975 .

[6]  W. Dunn.  SIMCA-3B, a pattern recognition program , 1987 .

[7]  S. Wold,et al.  Application of simca multivariate data analysis to the classification of gas chromatographic profiles of human brain tissues , 1981 .

[8]  Robert Sedgewick,et al.  Algorithms in C , 1990 .

[9]  Donald E. Myers,et al.  Correspondence analysis applied to environmental data sets: A study of Chautauqua Lake sediments , 1991 .

[10]  Brian Edward Cooper.  Statistics for experimentalists , 1969 .

[11]  S. Dharmavaram,et al.  Recent improvements to fantasia, a target transformation factor analysis program , 1986, Comput. Chem..

[12]  Wolfhard Wegscheider,et al.  Chemometrics Tutorials: Collected from Chemometrics and Intelligent Laboratory Systems - An International Journal, Volumes 1-5 , 1990 .

[13]  Paul J. Lewi,et al.  Spectral map analysis: Factorial analysis of contrasts, especially from log ratios , 1989 .

[14]  B. Kowalski,et al.  Partial least-squares regression: a tutorial , 1986 .

[15]  H. Vogel,et al.  Ch. K. Bayne, I. B. Rubin: Practical Experimental Designs and Optimization Methods for Chemists, VCH‐Verlagsgesellschaft Weinheim, Deerfield Beach‐Florida 1986. 205 Seiten, Preis: DM 110, — , 1987 .

[16]  L. Hammett,et al.  Physical organic chemistry , 1940 .

[17]  James F. Kerrigan.  From Fortran to C , 1991 .

[18]  W. Krzanowski.  Selection of Variables to Preserve Multivariate Data Structure, Using Principal Components , 1987 .

[19]  Diane D. Wolff,et al.  Pattern Recognition Approach to Data Interpretation , 1983, Springer US.

[20]  Desire L. Massart,et al.  The Interpretation of Analytical Chemical Data by the Use of Cluster Analysis , 1983 .

[21]  K. E. Thrane,et al.  Composition activity relationships — CARE: Part I. Exploratory multivariate analysis of elements, polycyclic aromatic hydrocarbons and mutagenicity in air samples , 1989 .

[22]  D. Steele,et al.  On the extraction of spectra of components from spectra of mixtures. A development in factor theory. II , 1990 .

[23]  W. J. Youden.  Statistical methods for chemists , 1951 .

[24]  Kenneth E. Iverson,et al.  Notation as a tool of thought , 1980, APLQ.

[25]  R. Brereton,et al.  Use of chemometric factor analysis for chromatographic integration: application to diode-array high-performance liquid chromatography of mixtures of chlorophyll a degradation products , 1993 .

[26]  Johnz Willett.  Similarity and Clustering in Chemical Information Systems , 1987 .

[27]  J. Devillers,et al.  A predictive structure-toxicity model with Daphnia magna , 1987 .

[28]  S. Piepponen,et al.  Data analysis of heavy metal pollution in the sea by using principal component analysis and partial least squares regression , 1989 .

[29]  I. I. Ioffe.  Application of Pattern Recognition to Catalytic Research , 1988 .

[30]  John Skilling,et al.  Maximum entropy method in nuclear magnetic resonance spectroscopy , 1985 .

[31]  Richard G. Brereton,et al.  Multivariate Pattern Recognition in Chemometrics: Illustrated by Case Studies , 1992 .

[32]  M. Stone.  Cross‐Validatory Choice and Assessment of Statistical Predictions , 1976 .

[33]  H. Könemann.  Quantitative structure-activity relationships in fish toxicity studies. Part 1: relationship for 50 industrial pollutants. , 1981, Toxicology.

[34]  S. Wold.  Cross-Validatory Estimation of the Number of Components in Factor and Principal Components Models , 1978 .

[35]  Bruce L. Bush,et al.  Sample-distance partial least squares: PLS optimized for many variables, with application to CoMFA , 1993, J. Comput. Aided Mol. Des..

[36]  A. D. Lunn,et al.  Computer-Interactive Data Analysis , 1991 .

[37]  R. Brereton,et al.  SAS (statistical analysis system) , 1986 .

[38]  Peter Murray-Rust,et al.  Computer retrieval and analysis of molecular geometry. II. Variance and its interpretation , 1978 .

[39]  Thomas C. O'Haver.  Teaching and learning chemometrics with MatLab , 1989 .

[40]  Philip H. Ramsey.  Data Fitting in the Chemical Sciences , 1994 .

[41]  W. T. Grandy.  Maximum entropy in action: Buck, Brian and Macaulay, Vincent A., 1991, 220 pp., Clarendon Press, Oxford, £30 pb, ISBN 0-19-8539630 , 1995 .

[42]  H. Joseph Newton.  S-PLUS for Unix and DOS , 1991 .

[43]  R. Brereton.  Chemometrics in analytical chemistry. A review , 1987 .

[44]  Ru-Qin Yu.  Chemometrics in China , 1992 .

[45]  Kurt Varmuza,et al.  Pattern recognition in chemistry , 1980 .

[46]  Jane L. Harvill,et al.  MINITAB statistical software, release 7.2 SUN-4 version , 1993 .

[47]  Richard G. Brereton,et al.  Chemometrics Tutorials II , 1992 .

[48]  Richard G. Brereton,et al.  Tutorial review. Object oriented programming on personal computers , 1994 .

[49]  Ian M. Graham.  Object-oriented methods , 1991 .

[50]  簡聰富,et al.  物件導向軟體之架構(Object-Oriented Software Construction)探討 , 1989 .

[51]  August Hansen.  Learn C Now , 1988 .

[52]  I. Jolliffe.  Discarding Variables in a Principal Component Analysis. Ii: Real Data , 1973 .

[53]  David S. Stephenson,et al.  Linear prediction and maximum entropy methods in NMR spectroscopy , 1988 .

[54]  Edmund R. Malinowski,et al.  Determination of the number of factors and the experimental error in a data matrix , 1977 .

[55]  J. Skilling,et al.  The application of ‘MaxEnt’ to high resolution mass spectrometry , 1992 .

[56]  R. Brereton,et al.  INVESTIGATION OF THE ALLOMERIZATION REACTION OF CHLOROPHYLL a: USE OF DIODE ARRAY HPLC, MASS SPECTROMETRY AND CHEMOMETRIC FACTOR ANALYSIS FOR THE DETECTION OF EARLY PRODUCTS , 1994 .

[57]  Kim H. Esbensen,et al.  UNSCRAMBLER, an interactive program for multivariate calibration and prediction , 1987 .

[58]  Paul Geladi,et al.  Analysis of multi-way (multi-mode) data , 1989 .

[59]  S. Clementi,et al.  PLS assessment of the performance of short‐term tests for carcinogens , 1988 .

[60]  J. U. Thomsen,et al.  Pattern recognition of the 1H NMR spectra of sugar alditols using a neural network , 1989 .

[61]  R. Brereton,et al.  Resolution of strongly overlapping two‐way multicomponent data by means of heuristic evolving latent projections , 1993 .

[62]  William H. Press,et al.  Numerical recipes , 1990 .

[63]  Olav M. Kvalheim,et al.  A general-purpose program for multivariate data analysis , 1987 .

[64]  Patrick Camilleri,et al.  Chiral chromatography and multivariate quantitative structure-property relationships of benzimidazole sulphoxides , 1993, J. Comput. Aided Mol. Des..

[65]  Stephen P. Gurden,et al.  Use of eigenvalues for determining the number of components in window factor analysis of spectroscopic and chromatographic data , 1995 .

[66]  Clifford H. Spiegelman,et al.  Statistical software packages for the macintosh , 1990 .

[67]  Herbert Schildt,et al.  C, the complete reference , 1987 .

[68]  Jure Zupan.  Computer Supported Spectroscopic Data Bases , 1986 .

[69]  Nils B. Vogt.  PARVUS — 50 programs for pattern recognition , 1989 .

[70]  Philip K. Hopke,et al.  Multielemental characterization of urban roadway dust , 1980 .

[71]  Svante Wold,et al.  Pattern recognition by means of disjoint principal components models , 1976, Pattern Recognit..

[72]  R. Brereton.  Spectral analysis of multivariate geochemical time series , 1987 .

[73]  J. Skilling,et al.  Maximum entropy signal processing in practical NMR spectroscopy , 1984, Nature.

[74]  M. Forina,et al.  Chemometrics for analytical chemistry , 1992 .

[75]  G. Nickless,et al.  Chemometric studies of the effect of toxic metals on plants: the use of response surface methodology to investigate the influence of Tl, Cd and Ag on the growth of cabbage seedlings. , 1988, Environmental pollution.

[76]  G. Kateman,et al.  Quality control in analytical chemistry , 1981 .

[77]  R. Brereton,et al.  Chemometric methods for the study of toxic metals on the growth of plants: use of experimental design and response surface methodology. , 1990 .

[78]  D. Massart.  Chemometrics: A Textbook , 1988 .

[79]  Brian D. Hudson,et al.  Pattern recognition display methods for the analysis of computed molecular properties , 1989, J. Comput. Aided Mol. Des..

[80]  Richard G. Brereton,et al.  Chemometrics: Applications of Mathematics and Statistics to Laboratory Systems , 1991 .

[81]  Wojtek J. Krzanowski,et al.  Cross-Validation in Principal Component Analysis , 1987 .

[82]  S. Wold,et al.  Application of principal component analysis to 13C NMR shifts of chalcones and their thiophene and furan analogues: A useful tool for the shift assignment and for the study of substituent effects , 1981 .