ecp: An R package for nonparametric multiple change point analysis of multivariate data

Journal of Statistical Software

Volumn 62, Issue 7, 2015, Pages 1-25

  James, Nicholas A ^a   Matteson, David S ^b  

^a School of Operations Research and Industrial Engineering   (United States)

^b Department of Statistical Science Cornell University ^*  (United States)

Author keywords

Cluster analysis; Multivariate time series; Signal processing

Indexed keywords

EID: 84921710883     PISSN: 15487660     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (30)

1. Akoglu L, Faloutsos C (2010). "Event Detection in Time Series of Mobile Communication Graphs." In Proceedings of Army Science Conference. 2010 Army Science Conference.
2. Bleakley K, Vert JP (2011). "The Group Fused Lasso for Multiple Change-Point Detection." Technical Report HAL-00602121, Bioinformatics Center (CBIO).
3. Bolton R, Hand D (2002). "Statistical Fraud Detection: A Review." Statistical Science, 17(3), 235-255.
4. Chang F, Qiu W, Zamar RH, Lazarus R, Wang X (2010). "clues: An R Package for Nonparametric Clustering Based on Local Shrinking." Journal of Statistical Software, 33(4), 1-16. URL http://www.jstatsoft.org/v33/i04/.
5. Chasalow S (2012). combinat: Combinatorics Utilities. R package version 0.0-8, URL http://CRAN.R-project.org/package=combinat.
6. Erdman C, Emerson JW (2007). "bcp: An R Package for Performing a Bayesian Analysis of Change Point Problems." Journal of Statistical Software, 23(3), 1-13. URL http://www.jstatsoft.org/v23/i03/.
7. Fowlkes EB, Mallows CL (1983). "A Method for Comparing Two Hierarchical Clusterings." Journal of the American Statistical Association, 78(383), 553-569.
8. Gandy A (2009). "Sequential Implementation of Monte Carlo Tests with Uniformly Bounded Resampling Risk." Journal of the American Statistical Association, 104(488), 1504-1511.
9. Genz A, Bretz F, Miwa T, Mi X, Leisch F, Scheipl F, Hothorn T (2014). mvtnorm: Multivariate Normal and t Distributions. R package version 1.0-0, URL http://CRAN.R-project.org/package=mvtnorm.
10. Gretton A, Borgwardt K, Rasch M, Schölkopf B, Smola A (2007). "A Kernel Method for the Two Sample Problem." In Advances in Neural Information Processing Systems 19, pp. 513-520. MIT Press.
11. Hoeffding W (1961). "The Strong Law of Large Numbers for U-Statistics." Technical Report 302, North Carolina State University, Department of Statistics.
12. Hubert L, Arabie P (1985). "Comparing Partitions." Journal of Classification, 2(1), 193-218.
13. Killick R, Eckley IA (2014). "changepoint: An R Package for Changepoint Analysis." Journal of Statistical Software, 58(3), 1-19. URL http://www.jstatsoft.org/v58/i03/.
14. Killick R, Fearnhead P, Eckley IA (2012). "Optimal Detection of Changepoints with a Linear Computational Cost." Journal of the American Statistical Association, 107(500), 1590-1598.
15. Lung-Yut-Fong A, Lévy-Leduc C, Cappé O (2011). “Homogeneity and Change-Point Detection Tests for Multivariate Data Using Rank Statistics.” arXiv:1107.1971 [math.ST], URL http://arxiv.org/abs/1107.1971.
16. Mampaey M, Vreeken J (2013). "Summarizing Categorical Data by Clustering Attributes." Data Mining and Knowledge Discovery, 26(1), 130-173.
17. Matteson DS, James NA (2014). "A Nonparametric Approach for Multiple Change Point Analysis of Multivariate Data." Journal of the American Statistical Association, 109(505), 334-345.
18. Morey LC, Agresti A (1984). "The Measurement of Classification Agreement: An Adjustment to the Rand Statistic for Chance Agreement." Educational and Psychological Measurement, 44(1), 33-37.
19. Muggeo VMR, Adelfio G (2011). "Efficient Change Point Detection for Genomic Sequences of Continuous Measurements." Bioinformatics, 27(2), 161-166.
20. Rand WM (1971). "Objective Criteria for the Evaluation of Clustering Methods." Journal of the American Statistical Association, 66(336), 846-850.
21. R Core Team (2014). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.
22. Ross GJ (2013). cpm: Sequential Parametric and Nonparametric Change Detection. R package version 1.1, URL http://CRAN.R-project.org/package=cpm.
23. Schauer K, Duong T, Bleakley K, Bardin S, Bornens M, Goud B (2010). "Probabilistic Density Maps to Study Global Endomembrane Organization." Nature Methods, 7(7), 560-566.
24. Sequeira K, Zaki M (2002). "ADMIT: Anomaly-Based Data Mining for Intrusions." In Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '02. ACM.
25. Székely GJ, Rizzo ML (2005). "Hierarchical Clustering Via Joint Between-Within Distances: Extending Ward's Minimum Variance Method." Journal of Classification, 22(2), 151-183.
26. Székely GJ, Rizzo ML (2010). "Disco Analysis: A Nonparametric Extension of Analysis of Variance." The Annals of Applied Statistics, 4(2), 1034-1055.
27. Talih M, Hengartner N (2005). "Structural Learning with Time-Varying Components: Tracking the Cross-Section of Financial Time Series." Journal of the Royal Statistical Society B, 67(3), 321-341.
28. Venables WN, Ripley BD (2002). Modern Applied Statistics with S. 4th edition. Springer-Verlag, New York. URL http://www.stats.ox.ac.uk/pub/MASS4.
29. Zeileis A, Kleiber C, Krämer W, Hornik K (2003). "Testing and Dating of Structural Changes in Practice." Computational Statistics & Data Analysis, 44(1-2), 109-123.
30. Zeileis A, Leisch F, Hornik K, Kleiber C (2002). “strucchange: An R Package for Testing for Structural Change in Linear Regression Models.” Journal of Statistical Software, 7(2), 1-38. URL http://www.jstatsoft.org/v07/i02/.