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Statistical thinking and technique for QSAR and related studies. Part I: General theory
Author(s) -
Stone Mervyn,
Jonathan Philip
Publication year - 1993
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.1180070603
Subject(s) - quantitative structure–activity relationship , computer science , management science , variety (cybernetics) , range (aeronautics) , statistical analysis , statistical model , artificial intelligence , statistical thinking , data science , epistemology , machine learning , mathematics , engineering , statistics , philosophy , aerospace engineering
Abstract The two parts of this paper form a critique of a variety of statistical techniques of actual or potential use in quantitative structure‐activity relationship (QSAR) studies and related fields. Part I explores the statistical thinking that is needed to underpin those techniques. Emphasis as placed on (a) the role of ‘exchangeability’ as an alternative to unrealistic statistical modelling and (b) the use of cross‐validation to limit self‐deception in the use of any particular technique. The problem of the almost unlimited range of molecular descriptors is seriously addressed. (Part II provides a concise critical review of methods‐some well‐established and some new.)