Dans la pratique, la plupart des statistiques de test ont une distribution de probabilite de forme inconnue. Generalement, on utilise leur loi asymptotique comme approximation de la vraie loi. Mais, si l'echelon dont on dispose n'est pas de taille suffisante cette approximation peut etre de...

We present a measure of the correlation between the education levels of spouses based on a bivariate ordered probit model. The change in this correlation over time can be measured while controlling for the large changes in the educational attainment levels. The model is estimated with data from...

In 2003, an industry-financed, government-administered buyback of trawl fishing permits and vessels took place on the US West Coast, resulting in the retirement of about one-third of the limited-entry trawl fleet. The lack of cost data in this fishery precludes an analysis of how the buyback has...

A new predictor-corrector interior point algorithm for solving monotone linear complementarity problems (LCP) is proposed, and it is shown to be superlinearly convergent with at least order 1.5, even if the LCP has no strictly complementary solution. Unlike Mizuno's recent algorithm, the fast...

There are serious reasons to assume that logarithmic stock returns are normally distributed, however, it is frequently denoted that the empirical distribution of stock returns characteristically deviates from a normal distribution : It is leptokurtic, it is peaked and it has thick tails.

This paper provides a test of monotonicity of a regression function. The test is based on the size of a "critical" bandwidth, the amount of smooting necessary to force a nonparametric regression estimate to be monotone. It is analogous to Silverman's test of multimodality in density estimation.

The factor GARCH model of Engle (1987) and the latent factor ARCH model of Diebold and Nerlove (1989) have become rather popular multivariate volatility parameterizations due to their parsimony, and the commonality in volatility movements across different financial series. Nevertheless, there is...

In this paper we present a meta-heuristic, known as a genetic algorithm, in order to solve the problems of (weigthed) independent set (IS), vertex covering (VC), set packing (SP) and maximum clique (MC).

We first analyse the general problem of admissible conditioning and next consider the evaluation of the loss of information when a non-admissible conditioning is used as an approximation of the exact posterior distribution. Considering the case of Fisher test, we evaluate from a Bayesian point...

When a model is nonlinear, boostrap testing can be expensive because of the need to perform at least one nonlinear estimation for every bootstrap sample. We show that it may be possible to reduce computational costs by performing only a fixed, small number of Newton steps or artificial...