Abstract
In this paper we discuss the problem on parametric and non parametric
estimation of the distributions generated by the Marshall-Olkin copula. This copula
comes from the Marshall-Olkin bivariate exponential distribution used in reliability
analysis. Through this copula we can extend the Marshall-Olkin distribution in order
to construct several bivariate survival functions. The cumulative distribution functions
of these distributions are not absolute continuous functions and they unknown
parameters are often not be obtained in explicit form. In particular we consider
the IFM method to find the Marshall-Olkin copula estimator, presenting the copula
likelihood function. We compare this procedure with a non parametric estimator of
the copula, the bivariate empirical copula, used to evaluate the copula goodness of
fit. The estimate procedures described are verified through several simulation. One
data-set is analyzed for a illustrative purpose.
| Lingua originale | English |
|---|---|
| Titolo della pubblicazione ospite | Conference proceeding of XLV Riunione Scientifica della Società Italiana di Statistica |
| Pagine | 1-8 |
| Numero di pagine | 8 |
| Stato di pubblicazione | Pubblicato - 2010 |
| Evento | XLV scientific meeting of the Italian Statistical Society - Padova Durata: 16 giu 2010 → 18 giu 2010 |
Convegno
| Convegno | XLV scientific meeting of the Italian Statistical Society |
|---|---|
| Città | Padova |
| Periodo | 16/6/10 → 18/6/10 |
Keywords
- Empirical Copula
- Marshall-Olkin copula
- Reliability analysis