PRIM analysis

Journal of Multivariate Analysis

Volumn 101, Issue 3, 2010, Pages 525-540

  Polonik, Wolfgang ^a   Wang, Zailong ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b NOVARTIS PHARMA AG   (Switzerland)

Author keywords

Asymptotics; Bump hunting; Data mining; Peeling + jittering; VC classes

Indexed keywords

EID: 72549096448     PISSN: 0047259X     EISSN: 10957243     Source Type: Journal    
DOI: 10.1016/j.jmva.2009.08.010     Document Type: Article

References (13)

1. Friedman J.H., and Fisher N.I. Bump hunting in high-dimensional data. Statist. Comput. 9 (1999) 123-143
2. Becker U., and Fahrmeier L. Bump hunting for risk: A new data mining tool and its applications. Comput. Statist. 16 3 (2001) 373-386
3. Cole S.W., Galic Z., and Zack J.A. Controlling false negative errors in microarray differential expression analysis: A PRIM approach. Bioinformatics 19 (2003) 1808-1816
4. Leblanc M., Jacobson J., and Crowley J. Partitioning and peeling for constructing prognostic groups. Stat. Methods Med. Res. 11 (2002) 247-274
5. Nannings B., Abu-Hanna A., and de Jonge E. Applying PRIM (patient rule induction method) and logistic regression for selecting high-risk subgroups in very elderly ICU patients. Int. J. Med. Inf. 77 (2008) 272-279
6. L. Wu, H. Chipman, Bayesian model-assisted PRIM algorithm, Technical Report, 2003
7. P. Wang, Y. Kim, J. Pollack, R. Tibshirani, Boosted PRIM with application to searching for oncogenic pathway of lung cancer, in: Proceedings of the 2004 IEEE Computational Systems Bioinformatics Conference (CBS 2004), 2004, pp. 604-609
8. Polonik W. Minimum volume sets and generalized quantile processes. Stochastics Process and Appl. 69 (1997) 1-24
9. Burman P., and Polonik W. Multivariate mode hunting: Data analytic tools with measures of significance. J. Multivariate Anal. 100 (2009) 1198-1218
10. Polonik W. Measuring mass concentrations and estimating density contour clusters - An excess mass approach. Ann. Statist. 23 (1995) 855-881
11. Tsybakov A.B. Optimal aggregation of classifiers in statistical learning. Ann. Statist. 32 (2004) 135-166
12. van der Vaart A.W., and Wellner J. Weak Convergence and Empirical Processes (1996), Springer, New York
13. Hastie T., Tibshirani R., and Friedman H.H. The Elements of Statistical Learning (2001), Springer, New York