Consistent multiple testing for change points

Kuo mei Chen; Arthur Cohen; Harold Sackrowitz

doi:10.1016/j.jmva.2011.04.012

Consistent multiple testing for change points

Kuo mei Chen, Arthur Cohen, Harold Sackrowitz

School of Arts and Sciences, Statistics

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

The change point problem for independent normal means is considered as a multiple testing problem. Two stepwise methods are considered. Namely, the binary segmentation method of Vostrikova (1981) [7] and the maximum residual down method of Cohen et al. (2009) [5]. Both of these methods are shown to be consistent. Consistent here means that as sample sizes tend to infinity, the probability of making an error (false rejection or false acceptance) tends to zero.

Original language	English (US)
Pages (from-to)	1339-1343
Number of pages	5
Journal	Journal of Multivariate Analysis
Volume	102
Issue number	10
DOIs	https://doi.org/10.1016/j.jmva.2011.04.012
State	Published - Nov 2011

All Science Journal Classification (ASJC) codes

Statistics and Probability
Numerical Analysis
Statistics, Probability and Uncertainty

Keywords

Binary sequential segmentation
Familywise error rate
Maximum residual down
Primary
Secondary
Stepdown procedures

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10.1016/j.jmva.2011.04.012

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title = "Consistent multiple testing for change points",

abstract = "The change point problem for independent normal means is considered as a multiple testing problem. Two stepwise methods are considered. Namely, the binary segmentation method of Vostrikova (1981) [7] and the maximum residual down method of Cohen et al. (2009) [5]. Both of these methods are shown to be consistent. Consistent here means that as sample sizes tend to infinity, the probability of making an error (false rejection or false acceptance) tends to zero.",

keywords = "Binary sequential segmentation, Familywise error rate, Maximum residual down, Primary, Secondary, Stepdown procedures",

author = "Chen, {Kuo mei} and Arthur Cohen and Harold Sackrowitz",

note = "Funding Information: Supported by NSF Grant DMS 0894547 and NSA Grant H-98230-06-0076 . ",

year = "2011",

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language = "English (US)",

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AU - Cohen, Arthur

AU - Sackrowitz, Harold

N1 - Funding Information: Supported by NSF Grant DMS 0894547 and NSA Grant H-98230-06-0076 .

PY - 2011/11

Y1 - 2011/11

N2 - The change point problem for independent normal means is considered as a multiple testing problem. Two stepwise methods are considered. Namely, the binary segmentation method of Vostrikova (1981) [7] and the maximum residual down method of Cohen et al. (2009) [5]. Both of these methods are shown to be consistent. Consistent here means that as sample sizes tend to infinity, the probability of making an error (false rejection or false acceptance) tends to zero.

AB - The change point problem for independent normal means is considered as a multiple testing problem. Two stepwise methods are considered. Namely, the binary segmentation method of Vostrikova (1981) [7] and the maximum residual down method of Cohen et al. (2009) [5]. Both of these methods are shown to be consistent. Consistent here means that as sample sizes tend to infinity, the probability of making an error (false rejection or false acceptance) tends to zero.

KW - Binary sequential segmentation

KW - Familywise error rate

KW - Maximum residual down

KW - Primary

KW - Secondary

KW - Stepdown procedures

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JO - Journal of Multivariate Analysis

JF - Journal of Multivariate Analysis

IS - 10

ER -

Consistent multiple testing for change points

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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