Vai ai contenuti. | Spostati sulla navigazione | Spostati sulla ricerca | Vai al menu | Contatti | Accessibilità

| Crea un account

Lunardon, Nicola - Pauli, Francesco - Ventura , Laura (2010) A note on empirical likelihoods derived from pairwise score functions. [Working Paper] WORKING PAPER SERIES, 16/2010 . , PADOVA

Full text disponibile come:

Documento PDF

Abstract (inglese)

Pairwise likelihood functions are convenient surrogates for the ordinary likelihood, useful when the latter is too di cult or even impractical to compute. One drawback of pairwise likelihood inference is that, for a multidimensional parameter of interest, the pairwise likelihood analogue of the likelihood ratio statistic does not have the standard chi-square asymptotic distribution. Invoking the theory of unbiased estimating functions, this paper proposes and discusses a computationally and theoretically attractive approach based on the derivation of empirical likelihood functions from the pairwise scores. This approach produces alternatives to the pairwise likelihood ratio statistic, which allow reference to the usual asymptotic chi-square distribution useful when the elements of the Godambe information are troublesome to evaluate or in the presence of large datasets with relative small sample sizes. Monte Carlo studies are performed in order to assess the finite-sample performance of the proposed empirical pairwise likelihoods

Statistiche Download - Aggiungi a RefWorks
Tipo di EPrint:Working Paper
Anno di Pubblicazione:Novembre 2010
Informazioni aggiuntive:Pubblicato anche in: Journal of Statistical Computation and Simulation, DOI: 10.1080/00949655.2012.661431
Parole chiave (italiano / inglese):Composite likelihood, Empirical likelihood, First-order asymptotic, Likelihood ratio statistic, Unbiased estimating function, Pairwise likelihood, Godambe information, Multivariate extreme values, Correlated bunary data
Settori scientifico-disciplinari MIUR:Area 13 - Scienze economiche e statistiche > SECS-S/01 Statistica
Struttura di riferimento:Dipartimenti > Dipartimento di Scienze Statistiche
Codice ID:8793
Depositato il:14 Mag 2015 17:58
Simple Metadata
Full Metadata
EndNote Format

Download statistics

Solo per lo Staff dell Archivio: Modifica questo record