Title of article :
Toward Bayesian chemometrics—A tutorial on some recent advances Review Article
Author/Authors :
Hongshu Chen، نويسنده , , Bhavik R. Bakshi، نويسنده , , Prem K. Goel، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2007
Pages :
16
From page :
1
To page :
16
Abstract :
Chemometrics is increasingly being perceived as a maturing science. While this perception seems to be true with regards to the traditional methods and applications of chemometrics, this article argues that advances in instrumentation, computation, and statistical theory may combine to drive a resurgence in chemometrics research. Previous surges in chemometrics research activity were driven by the development of new ways of making better use of available information. Bayesian statistics can further enhance the ability to use domain specific information to obtain more accurate and useful models, and presents many research opportunities as well as challenges.
Keywords :
Principal component analysis (PCA) , Bayesian statistics , Regression , maximum likelihood , Latent variables , Partial least squares (PLS)
Journal title :
Analytica Chimica Acta
Serial Year :
2007
Journal title :
Analytica Chimica Acta
Record number :
1031233
Link To Document :
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