Please use this identifier to cite or link to this item: http://arl.liuc.it/dspace/handle/2468/4317
Title: Modelling the dependence in multivariate longitudinal data by pair copula decomposition
Authors: Nai Ruscone, Marta
Osmetti, Silvia Angela
Issue Date: 2014
Publisher: CMStatistics and CFEnetwork
Bibliographic citation: Nai Ruscone Marta, Osmetti Silvia Angela (2014), Modelling the dependence in multivariate longitudinal data by pair copula decomposition. In: 8th International Conference on Computational and Financial Econometrics (CFE 2014) and 7th International Conference of the ERCIM (European Research Consortium for Informatics and Mathematics) Working Group on Computational and Methodological Statistics (ERCIM 2014), p. 177. ISBN 978-84-937822-4-5.
Abstract: A new flexible way of modeling the dependence between the components of non-normal multivariate longitudinal-data is proposed by using the copula approach. The presence of longitudinal data is increasing in the scientific areas where several variables are measured over a sample of statistical units at different times, showing two types of dependence: between variables and across time. In order to account both type of dependence the proposed model considers two levels of analysis. First given a specific time, we model the relations of variables using copula. The use of the copula allows us to relax the assumption of normality. In the second level, each longitudinal series, corresponding to a given response over time, is modelled separately using a pair copula decomposition to relate the distributions of the variables describing the observation taken in different times. The use of the pair copula decomposition allows us to overcome the problem of the multivariate copulae used in the literature which suffer from rather inflexible structures in high dimension. The result is a new extreme flexible multivariate longitudinal model, which overcomes the problem of modelling simultaneous dependence between two or more non-normal time-series.
URI: http://arl.liuc.it/dspace/handle/2468/4317
Journal/Book: 8th International Conference on Computational and Financial Econometrics (CFE 2014) and 7th International Conference of the ERCIM (European Research Consortium for Informatics and Mathematics) Working Group on Computational and Methodological Statistics (ERCIM 2014)
ISBN: 978-84-937822-4-5
Appears in Collections:Contributo in atti di convegno

Files in This Item:
File Description SizeFormat 
4317.pdf
  Restricted Access
184,24 kBAdobe PDFView/Open Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.