Multiscale change point inference

We introduce a new estimator, the simultaneous multiscale change point estimator SMUCE, for the change point problem in exponential family regression. An unknown step function is estimated by minimizing the number of change points over the acceptance region of a multiscale test at a level α. The pro...

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Veröffentlicht in:	Journal of the Royal Statistical Society. Series B, Statistical methodology Statistical methodology, 2014-06, Vol.76 (3), p.495-580
Hauptverfasser:	Frick, Klaus, Munk, Axel, Sieling, Hannes
Format:	Artikel
Sprache:	eng
Schlagworte:	Asymptotic properties Change point regression Computational efficiency Computational methods Confidence Confidence intervals Dynamic programming Estimating Estimators Exponential families Family genetic engineering Honest confidence sets Inference Multiscale methods Probability Regression analysis Simulation spectroscopy Statistical analysis Statistical methods Statistics Step functions Studies
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