In this paper we describe how to conduct a change-point analysis when dealing with time ordered data that are measured on an ordinal scale. In order to treat such time series we propose to employ a fuzzy coding i.e. the ordinal scale is converted into a fuzzy variable. Then, to detect the number and location of change points we employ in the framework of Atheoretical Regression Trees (ART) a deviation measure for fuzzy variables. The proposal is illustrated by an application to a real ordinal time series.
Regression trees for change point analysis of ordinal time series / Cappelli, Carmela; DI IORIO, Francesca; P., D'Urso. - In: QUADERNI DI STATISTICA. - ISSN 1594-3739. - STAMPA. - 14:(2012), pp. 57-60.
Regression trees for change point analysis of ordinal time series
CAPPELLI, CARMELA;DI IORIO, FRANCESCA;
2012
Abstract
In this paper we describe how to conduct a change-point analysis when dealing with time ordered data that are measured on an ordinal scale. In order to treat such time series we propose to employ a fuzzy coding i.e. the ordinal scale is converted into a fuzzy variable. Then, to detect the number and location of change points we employ in the framework of Atheoretical Regression Trees (ART) a deviation measure for fuzzy variables. The proposal is illustrated by an application to a real ordinal time series.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
