Zobrazeno 1 - 10
of 151
pro vyhledávání: '"A. Keziou"'
We consider semiparametric moment condition models invariant to transformation groups. The parameter of interest is estimated by minimum empirical divergence approach, introduced by Broniatowski and Keziou (2012). It is shown that the minimum empiric
Externí odkaz:
http://arxiv.org/abs/1904.11823
Autor:
Bouzebda, Salim, Keziou, Amor
Publikováno v:
Journal of Nonparametric Statistics; Dec2024, Vol. 36 Issue 4, p1192-1224, 33p
Autor:
Keziou, Amor, Regnault, Philippe
We derive independence tests by means of dependence measures thresholding in a semiparametric context. Precisely, estimates of phi-mutual informations, associated to phi-divergences between a joint distribution and the product distribution of its mar
Externí odkaz:
http://arxiv.org/abs/1508.04671
Publikováno v:
In Digital Signal Processing May 2020 100
Publikováno v:
Communications in Statistics. Theory and Methods -42 (2013), no. 12, 2245-2270
In the present paper we propose a new estimator of entropy based on smooth estimators of quantile density. The consistency and asymptotic distribution of the proposed estimates are obtained. As a consequence, a new test of normality is proposed. A sm
Externí odkaz:
http://arxiv.org/abs/1110.3436
Autor:
Broniatowski, Michel, Keziou, Amor
We consider the minimization problem of $\phi$-divergences between a given probability measure $P$ and subsets $\Omega$ of the vector space $\mathcal{M}_\mathcal{F}$ of all signed finite measures which integrate a given class $\mathcal{F}$ of bounded
Externí odkaz:
http://arxiv.org/abs/1003.5457
Autor:
Broniatowski, Michel, Keziou, Amor
We introduce estimation and test procedures through divergence minimiza- tion for models satisfying linear constraints with unknown parameter. These procedures extend the empirical likelihood (EL) method and share common features with generalized emp
Externí odkaz:
http://arxiv.org/abs/1002.0730
Autor:
Broniatowski, Michel, Keziou, Amor
We introduce estimation and test procedures through divergence optimization for discrete or continuous parametric models. This approach is based on a new dual representation for divergences. We treat point estimation and tests for simple and composit
Externí odkaz:
http://arxiv.org/abs/0811.3705
Autor:
Broniatowski, Michel, Keziou, Amor
We introduce estimation and test procedures through divergence minimization for models satisfying linear constraints with unknown parameter. Several statistical examples and motivations are given. These procedures extend the empirical likelihood (EL)
Externí odkaz:
http://arxiv.org/abs/0811.3477
Autor:
Bouzebda, Salim, Keziou, Amor
Publikováno v:
Kybernetika- 46 (2010), no. 1, 178-201
We introduce new estimates and tests of independence in copula models with unknown margins using $\phi$-divergences and the duality technique. The asymptotic laws of the estimates and the test statistics are established both when the parameter is an
Externí odkaz:
http://arxiv.org/abs/0806.4864