Application of modified information criterion to multiple change point problems

Journal of Multivariate Analysis

Volumn 97, Issue 10, 2006, Pages 2221-2241

  Pan, Jianmin ^a   Chen, Jiahua ^b  

^a ST JUDE CHILDREN S RESEARCH HOSPITAL   (United States)

^b UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Consistency; Convergence rate; Limiting distribution; Model complexity; Multiple change points; Regular parametric model

Indexed keywords

EID: 33749126802     PISSN: 0047259X     EISSN: 10957243     Source Type: Journal    
DOI: 10.1016/j.jmva.2006.05.009     Document Type: Article

References (25)

1. Akaike H. Information theory and an extension of the maximum likelihood principle. In: Petrov B.N., and Csaki E. (Eds). Second International Symposium on Information Theory (1973), Akademiai Kiado, Budapest 267-281
2. Bai J., and Perron P. Estimating and testing linear models with multiple structural changes. Econometrica 66 (1998) 47-78
3. Barry D., and Hartigan J.A. Product partition models for change point problems. Ann. Statist. 20 (1992) 260-279
4. J. Chen, A.K. Gupta, J. Pan, Information Criterion and change point problem in regular models, Sankhyover(a, -), 2006, accepted for publication.
5. Chernoff S., and Zacks S. Estimating the current mean of a normal distribution which is subjected to changes in time. Ann. Math. Statist. 35 (1964) 999-1018
6. Csörgö M., and Horváth L. Limit Theorems in Change-Point Analysis (1997), Wiley, New York
7. Csörgö M., and Révész P. Strong Approximations in Probability and Statistics (1981), Academic Press, New York
8. Fu Y.-X., and Curnow R.N. Maximum likelihood estimation of multiple change points. Biometrika 77 (1990) 563-573
9. Gombay E., and Horváth L. An application of U-statistics to change-point analysis. Acta. Sci. Math. 60 (1995) 345-357
10. Inclán C., and Tiao G.C. Use of sums of squares for retrospective detection of changes of variance. J. Amer. Statist. Assoc. 89 (1994) 913-923
11. Lai T.-L., Liu H., and Xing H. Autoregressive models with piecewise constant volatility and regression parameters. Statist. Sinica 15 (2005) 279-301
12. Lavielle M. Detection of multiple changes in a sequence of dependent variables. Stochastic Process. Appl. 83 (1999) 79-102
13. Lee C.-B. Nonparametric multiple change-point estimators. Statist. Probab. Lett. 27 (1996) 295-304
14. Lee C.-B. Bayesian estimation of the number of change points. Statist. Sinica 8 (1998) 923-939
15. Ninomiya Y. Information criterion for Gaussian change-point model. Statist. Probab. Lett. 72 (2005) 237-247
16. Page E.S. Continuous inspection schemes. Biometrika 41 (1954) 100-116
17. Page E.S. A test for a change in a parameter occurring at an unknown point. Biometrika 42 (1955) 523-526
18. Schwarz G. Estimating the dimension of a model. Ann. Statist. 6 (1978) 461-464
19. Sen P.K., and Singer J.M. Large Sample Methods in Statistics: An Introduction with Applications (1993), Chapman & Hall, New York
20. Serfling R.J. Approximation Theorems of Mathematical Statistics (1980), Wiley, New York
21. Siegmund D. Model selection in irregular problems: applications to mapping quantitative trait loci. Biometrika 91 (2004) 785-800
22. Wald A. Note on the consistency of the maximum likelihood estimate. Ann. Math. Statist. 20 (1949) 595-601
23. Yao Y.-C. Estimation of a noisy discrete-time step function: Bayes and empirical Bayes approaches. Ann. Statist. 12 (1984) 1434-1447
24. Yao Y.-C. Estimating the number of change-point via Schwarz' criterion. Statist. Probab. Lett. 6 (1988) 181-189
25. Yao Y.-C., and Au S.T. Least-squares estimation of a step function. Sankhyover(a, -) Ser. A 51 (1989) 370-381