Slope heuristics for multiple change-point models
With regard to multiple change-point models, much effort has been devoted to the selection of the number of change points. But, the proposed approaches are either dedicated to specific segment models or give unsatisfactory results for short or medium length sequences. We propose to apply the slope heuristic, a recently proposed non-asymptotic penalized likelihood criterion, for selecting the number of change points. In particular we apply the data-driven slope estimation method, the key point being to define a relevant penalty shape. The proposed approach is illustrated using two benchmark data sets.
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dig-cirad-fr-5786382022-04-15T12:54:39Z http://agritrop.cirad.fr/578638/ http://agritrop.cirad.fr/578638/ Slope heuristics for multiple change-point models. Guédon Yann. 2015. In : Proceedings of the 30th International Workshop on Statistical Modelling. Friedl Herwig (ed.), Wagner Helga (ed.). Linz : Statistical Modelling Society, 103-106. International Workshop on Statistical Modelling. 30, Linz, Autriche, 6 Juillet 2015/10 Juillet 2015. Researchers Slope heuristics for multiple change-point models Guédon, Yann eng 2015 Statistical Modelling Society Proceedings of the 30th International Workshop on Statistical Modelling U10 - Informatique, mathématiques et statistiques With regard to multiple change-point models, much effort has been devoted to the selection of the number of change points. But, the proposed approaches are either dedicated to specific segment models or give unsatisfactory results for short or medium length sequences. We propose to apply the slope heuristic, a recently proposed non-asymptotic penalized likelihood criterion, for selecting the number of change points. In particular we apply the data-driven slope estimation method, the key point being to define a relevant penalty shape. The proposed approach is illustrated using two benchmark data sets. conference_item info:eu-repo/semantics/conferenceObject Conference info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/578638/1/Guedon2015b.pdf text cc_by_nc_nd info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-nd/4.0/ |
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U10 - Informatique, mathématiques et statistiques U10 - Informatique, mathématiques et statistiques Guédon, Yann Slope heuristics for multiple change-point models |
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With regard to multiple change-point models, much effort has been devoted to the selection of the number of change points. But, the proposed approaches are either dedicated to specific segment models or give unsatisfactory results for short or medium length sequences. We propose to apply the slope heuristic, a recently proposed non-asymptotic penalized likelihood criterion, for selecting the number of change points. In particular we apply the data-driven slope estimation method, the key point being to define a relevant penalty shape. The proposed approach is illustrated using two benchmark data sets. |
| format |
conference_item |
| topic_facet |
U10 - Informatique, mathématiques et statistiques |
| author |
Guédon, Yann |
| author_facet |
Guédon, Yann |
| author_sort |
Guédon, Yann |
| title |
Slope heuristics for multiple change-point models |
| title_short |
Slope heuristics for multiple change-point models |
| title_full |
Slope heuristics for multiple change-point models |
| title_fullStr |
Slope heuristics for multiple change-point models |
| title_full_unstemmed |
Slope heuristics for multiple change-point models |
| title_sort |
slope heuristics for multiple change-point models |
| publisher |
Statistical Modelling Society |
| url |
http://agritrop.cirad.fr/578638/ http://agritrop.cirad.fr/578638/1/Guedon2015b.pdf |
| work_keys_str_mv |
AT guedonyann slopeheuristicsformultiplechangepointmodels |
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