5) Publications

J-E Dazard, PhD edited this page Mar 2, 2018 · 15 revisions

Methodology Papers of PRIMsrc

(open access, by chronological order)

  1. Dazard J-E., Rao J.S. Variable Selection Strategies for High-Dimensional Survival Bump Hunting using Recursive Peeling Methods. [2018 (in prep)].

  2. Dazard J-E., Choe M., Leblanc M., Rao J.S. Cross-validation and Peeling Strategies for Survival Bump Hunting Survival using Recursive Peeling Methods. Statistical Analysis and Data Mining. 2016;9(1):12-42. The American Statistical Association (ASA) Affiliated Data Science Journal (doi:10.1002/sam.11301). Also available at: The Cornell University Library Archives arXiv v1:v8 (2015-01-16 : 2015-11-20).

  3. Dazard J-E., Choe M., LeBlanc M., Rao J.S. R package PRIMsrc: Bump Hunting by Patient Rule Induction Method for Survival, Regression and Classification. Joint Statistical Meetings, Section for Statistical Programmers and Analysts, Seattle, WA. USA. 2015. JSM Proceedings, American Statistical Association. 2015;650-664.

  4. Dazard J-E., Choe M., LeBlanc M., Rao J.S. Cross-Validated Survival Bump Hunting using Recursive Peeling Methods. Joint Statistical Meetings, Section for survival methods for risk estimation/prediction, Boston, MA. USA. 2014. JSM Proceedings, American Statistical Association. 2014;3366-3380.

Application Papers using PRIMsrc

  1. Dazard J-E., Choe M, Pawitan Y., Rao J.S. Identification and Characterization of Informative Prognostic Subgroups by Survival Bump Hunting. [2018 (in prep)].

Other Methodology Papers and Publication History of Seminal Papers

  1. Diaz-Pachon D.A., Saenz J.P., Rao J.S., Dazard J-E. Mode Hunting through Active Information. Applied Stochastic Models in Business and Industry 2018 (in press).

  2. Diaz-Pachon D.A., Rao J.S., Dazard J-E. On the Explanatory Power of Principal Components. [2017 (submitted)]. Also available at: The Cornell University Library Archives arXiv v1 (2014-04-19).

  3. Diaz-Pachon D.A., Dazard J-E. and Rao J.S. Unsupervised Bump Hunting Using Principal Components. In: Ahmed SE, editor. Big and Complex Data Analysis: Methodologies and Applications. Contributions to Statistics, vol. Edited Refereed Volume. Springer International Publishing, Cham Switzerland (2017), 325-345.

  4. Diaz-Pachon D.A., Rao J.S., Dazard J-E., editors. Optimization of the Patient Rule Induction Method (PRIM) under normality. Complex Data Modeling and Computationally Intensive Statistical Methods for Estimation and Prediction; 2013; Milan, Italy: S.Co. Proceedings. 2013.

  5. Dazard J-E., Rao J.S., Markowitz S. Local sparse bump hunting reveals molecular heterogeneity of colon tumors. Statistics in medicine. 2012;31(11-12):1203-1220.

  6. Dazard J-E., Rao J.S. Local Sparse Bump Hunting. J. Comput. Graph. Stat. 2010;19(4):900-29.

  7. Yi C., Huang J. Semismooth Newton Coordinate Descent Algorithm for Elastic-Net Penalized Huber Loss Regression and Quantile Regression. J. Comp Graph. Statistics (2016), DOI: 10.1080/10618600.2016.1256816.

  8. Polonik W. and Wang Z. Prim Analysis. J. Multivariate Anal. 2010;101(3):525–540.

  9. Burman P. and Polonik W. Multivariate mode hunting: data analytic tools with measures of significance. J. Multivariate Anal. 2009;100:1198–1218.

  10. Wu L. and Chipman H. Bayesian Model-Assisted PRIM Algorithm. Departments of Statistics and Actuarial Science, University of Waterloo, Technical Report, 2003.

  11. Friedman J. and Fisher N. Bump hunting in high-dimensional data. Stat. Comput. 1999;9(2):123–143..

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