We establish the strong consistency and asymptotic normality of the quasi-maximum likelihood estimator of the parameters of a class of multivariate GARCH processes. The conditions are mild and coincide with the minimal ones in the univariate case. In particular, contrary to the current...

We present a new method for estimating the frontier of a multidimensional sample. The estimator is based on a kernel regression on high order moments. It is assumed that the order of the moments goes to infinity while the bandwidth of the kernel goes to zero. The consistency of the estimator is...

We derive conditions under which structural econometric models that rely on numerical computation of equilibria produce consistent and asymptotically normal parameter estimates. The conditions are weaker than those required for the application of the implicit function theory.

In this paper, based on moment-type and location invariant Hill estimators, a new kind of location invariant moment-type extreme value index estimator is proposed. The weak and strong consistency of the estimator are discussed. The asymptotic expansion of the estimator and its distribution are...

We present a new method for estimating the endpoint of a unidimensional sample when the distribution function decreases at a polynomial rate to zero in the neighborhood of the endpoint. The estimator is based on the use of high-order moments of the variable of interest. It is assumed that the...

In their recent paper, Wang and Leblanc (Ann Inst Stat Math 60:883–900, <CitationRef CitationID="CR17">2008</CitationRef>) have shown that the second-order least squares estimator (SLSE) is more efficient than the ordinary least squares estimator (OLSE) when the errors are independent and identically distributed with non zero third...</citationref>

We construct and investigate a (1−α)-upper prediction bound for a future observation of a cyclic Poisson process using past data. A normal based confidence interval for our upper prediction bound is established. A comparison of the new prediction bound with a simpler nonparametric prediction...

In the present paper, we propose a Palm likelihood approach as a general estimating principle for stationary point processes in <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$\mathbf{R}^d$$</EquationSource> </InlineEquation> for which the density of the second-order factorial moment measure is available in closed form or in an integral representation. Examples of such...</equationsource></inlineequation>