2026-06-27T22:59:40Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/351602023-08-11T07:00:46Zcom_20.500.14352_14col_20.500.14352_15

Biswas, Atanu Pardo Llorente, María del Carmen 2023-06-19T15:01:46Z 2023-06-19T15:01:46Z 2014 1133-0686 10.1007/s11749-014-0364-8 https://hdl.handle.net/20.500.14352/35160 http://link.springer.com/article/10.1007%2Fs11749-014-0364-8 http://link.springer.com For stationary time series of nominal categorical data or ordinal categorical data (with arbitrary ordered numberings of the categories), autocorrelation does not make much sense. Biswas and Guha (J Stat Plan Infer 139:3076–3087, 2009a) used mutual information as a measure of association and introduced the concept of auto-mutual information in this context. In this present paper, we introduce general auto-association measures for this purpose and study several special cases. Theoretical properties and simulation results are given along with two illustrative real data examples. eng restricted access Auto-association measures for stationary time series of categorical data. journal article