Modelling the dependence in multivariate longitudinal data by pair copula decomposition

Marta Nai Ruscone, Silvia Angela Osmetti

Risultato della ricerca: Contributo in libroContributo a convegno

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.
Lingua originaleEnglish
Titolo della pubblicazione ospiteBook of Abstracts CFE 2014 8th International Conference on Computational anf Financial Econometrics, ERCIM 2014 tth International Conference of the ERCIM Working Grup on Computational and Methodological Statistics
Pagine177
Numero di pagine1
Stato di pubblicazionePubblicato - 2014
Evento8th 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) - Pisa
Durata: 6 dic 20149 dic 2014

Convegno

Convegno8th 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)
CittàPisa
Periodo6/12/149/12/14

Keywords

  • D-vine
  • longitudinal model
  • multivariate distribution
  • pair copula construction

Fingerprint

Entra nei temi di ricerca di 'Modelling the dependence in multivariate longitudinal data by pair copula decomposition'. Insieme formano una fingerprint unica.

Cita questo