Biswas, AtanuPardo Llorente, María del Carmen2023-06-192023-06-1920141133-068610.1007/s11749-014-0364-8https://hdl.handle.net/20.500.14352/35160For 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.engjournal articlehttp://link.springer.com/article/10.1007%2Fs11749-014-0364-8http://link.springer.comrestricted access519.22Power divergenceHavrda–Charvat entropyARMA Categorical data analysisAuto-associationEstadística matemática (Matemáticas)1209 Estadística