NIR and mass spectra classification: Bayesian methods for wavelet-based feature selection

Chemometrics and Intelligent Laboratory Systems

Volumn 77, Issue 1-2 SPEC. ISS., 2005, Pages 139-148

  Vannucci, Marina ^a   Sha, Naijun ^b   Brown, Philip J ^c  

^a TEXAS A AND M UNIVERSITY   (United States)

^b UNIVERSITY OF TEXAS AT EL PASO   (United States)

^c UNIVERSITY OF KENT   (United Kingdom)

Author keywords

Bayesian variable selection; Discrimination; Multinomial probit models; NIR spectra; Proteomic data; Wavelet transforms

Indexed keywords

ARTICLE; BAYES THEOREM; CLASSIFICATION; CONTROLLED STUDY; DESORPTION; FEMALE; HUMAN; IONIZATION; MAJOR CLINICAL STUDY; MASS SPECTROMETRY; NEAR INFRARED SPECTROSCOPY; OVARY CANCER; PRIORITY JOURNAL; SERUM; SURFACE ENHANCED LASER DESORPTION IONIZATION TIME OF FLIGHT MASS SPECTROMETRY; THEORETICAL MODEL;

EID: 19344369995     PISSN: 01697439     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.chemolab.2004.10.009     Document Type: Article

References (27)

1. B.G. Osborne, T. Fearn, and P.H. Hindle Practical NIR spectroscopy 1993 Longman Harlow, U.K
2. W.J. Krzanowski, P. Jonathan, W.V. McCarthy, and M.R. Thomas Discriminant analysis with singular covariance matrices: methods and applications to spectroscopic data Applied Statistics 44 1995 105 115
3. E.F. Petricoin, A.M. Ardekani, B.A. Hitt, P.J. Levine, V.A. Fusaro, S.M. Steinberg, G.B. Mills, C. Simone, D.A. Fishman, E.C. Kohn, and L.A. Liotta Use of proteomic patterns in serum to identify ovarian cancer Lancet 359 2002 572 577
4. B. Wu, T. Abbott, D. Fishman, W. McCurray, G. Mor, K. Stone, D. Ward, K. Williams, and H. Zhao Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data Bioinformatics 19 2003 1636 1643
5. Y. Qu, B.L. Adam, M. Thornquist, J.D. Potter, M.L. Thompson, Y. Yasui, J. Davis, P.F. Schellhammer, L. Cazares, M.A. Clements, G.L. Wright Jr., and Z. Feng Data reduction using a discrete wavelet transform in discriminant analysis of very high dimensionality data Biometrics 59 2003 143 151
6. D. Donoho, and I. Johnstone Ideal spatial adaption via wavelet shrinkage Biometrika 81 1994 425 455
7. D. Donoho, and I. Johnstone Minimax estimation via wavelet shrinkage Annals of Statistics 26 3 1998 879 921
8. W. Chang, S. Kim, and B. Vidakovic Wavelet-based estimation of a discriminant function Applied Stochastic Models in Business and Industry 19 2003 185 198
9. P.J. Brown, T. Fearn, and M. Vannucci Multivariate Bayesian variable selection and prediction Journal of the American Statistical Association 96 2001 398 408
10. J.S. Morris, M. Vannucci, P.J. Brown, and R.J. Carroll Wavelet-based nonparametric modeling of hierarchical functions in colon carcinogenesis (with discussion) Journal of the American Statistical Association 98 2003 573 597
11. N. Sha, M. Vannucci, M.G. Tadesse, P.J. Brown, I. Dragoni, N. Davies, T.C. Roberts, A. Contestabile, N. Salmon, C. Buckley, and F. Falciani Bayesian variable selection in multinomial probit models to identify molecular signatures of disease stage Biometrics 60 3 2004 812 819
12. 2(R) Transactions of the American Mathematical Society 315 1 1989 69 87
13. I. Daubechies Ten lectures on wavelets SIAM, Conference Series vol. 61 1992
14. A. Antoniadis, J. Bigot, and T. Sapatinas Wavelet estimators in non-parametric regression: a comparative simulation study Journal of Statistical Software 6 2001 1 83
15. M. Vannucci, P.J. Brown, and T. Fearn A decision theoretical approach to wavelet regression on curves with a high number of regressors Journal of Statistical Planning and Inference 112 1-2 2003 195 212
16. J.H. Albert, and S. Chib Bayesian analysis of binary and polychotomous response data Journal of the American Statistical Association 88 1993 669 679
17. M. Vannucci, and F. Corradi Covariance structure of wavelet coefficients: theory and models in a Bayesian perspective Journal of the Royal Statistical Society. Series B 61 4 1999 971 986
18. P.J. Brown, M. Vannucci, and T. Fearn Multivariate Bayesian variable selection and prediction Journal of the Royal Statistical Society. Series B 60 3 1998 627 641
19. P.J. Brown, M. Vannucci, and T. Fearn Bayesian wavelength selection in multicomponent analysis Journal of Chemometrics 12 1998 173 182
20. P.J. Brown, M. Vannucci, and T. Fearn Bayes model averaging with selection of regressors Journal of the Royal Statistical Society. Series B 64 3 2002 519 536
21. T. Fearn, P.J. Brown, and P. Besbeas A Bayesian decision theory approach to variable selection for discrimination Statistics and Computing 12 3 2002 253 260
22. D.V. Lindley A statistical paradox Biometrika 44 1957 187 192
23. G. Alexe, S. Alexe, L.A. Liotta, E. Petricoin, M. Reiss, and P.L. Hammer Ovarian cancer detection by logical analysis of proteomic data Proteomics 4 2004 766 783
24. K.A. Baggerly, J.S. Morris, and K.R. Coombes Reproducibility of SELDI-TOF protein patterns in serum: comparing data sets from different experiments Bioinformatics 20 2004 777 785
25. R.B. Cleveland, W.S. Cleveland, J.E. McRae, and I. Terpenning STL: a seasonal trend decomposition procedure based on LOESS (with discussion) Journal of Official Statistics 6 1990 3 73
26. H. Ojelund, P.J. Brown, H. Madsen, and P. Thyregod Prediction based on mean subset Technometrics 44 2002 369 378
27. T.T. Cai Adaptove wavelet estimation: a block thresholding and oracle inequality approach Annals of Statistics 27 1999 898 924