Aggregation and long memory: recent developments

Remigijus Leipus (1) , Anne Philippe (2) , Donata Puplinskaite (1, 2) , Donatas Surgailis (1)

1 Vilnius Institute of Mathematics and Informatics
2 LMJL - Laboratoire de Mathématiques Jean Leray

It is well-known that the aggregated time series might have very different properties from those of the individual series, in particular, long memory. At the present time, aggregation has become one of the main tools for modelling of long memory processes. We review recent work on contemporaneous aggregation of random-coefficient AR(1) and related models, with particular focus on various long memory properties of the aggregated process.

Mots clés: disaggregation; Random-coefficient AR(1); contemporaneous aggregation; long memory; infinite variance; mixed moving average; scaling limit; intermediate process; autoregressive random fields; anisotropic long memory; disaggregation.

Domaines: Statistiques [math.ST]; Théorie [stat.TH]

Remigijus Leipus, Anne Philippe, Donata Puplinskaite, Donatas Surgailis. Aggregation and long memory: recent developments. 2013. ⟨hal-00834034⟩