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We determine which nilpotent orbits in E6 have closures which are normal varieties and which do not. At the same time we are able to verify a conjecture in [E. Sommers, Comm. Math. Univ. Sancti Pauli ...
For the classical groups, Kraft and Procesi have resolved the question of which nilpotent orbits have closures that are normal and which do not, with the exception of the very even orbits in D2l that ...
Stochastic simulators such as Monte-Carlo estimators are widely used in science and engineering to study physical systems through their probabilistic representation. Global sensitivity analysis aims t...
Many mathematical models involve input parameters, which are not precisely known. Global sensitivity analysis aims to identify the parameters whose uncertainty has the largest impact on the variabilit...
In this paper we considered a general seasonal time series model with K-dependent and \rambda-dependent errors, which are new concepts of dependence. In this model we derived consistency and asymptoti...
We study the properties of variational Bayes approximations for exponential family mod-els with missing values. It is shown that the iterative algorithm for obtaining the varia-tional Bayesian estimat...
In this work is obtained an explicit form for the perturbation effect on the matrix of regression coefficients on the optimal solution in multiresponse surface methodology. Then, the sensitivity analy...
Variational methods for parameter estimation are an activere-search area, potentially offering computationally tractable heuristics with theoretical performance bounds. We build on recent work that ap...
It is shown the almost sure convergence and asymptotical normality of a generalization of Kesten's stochastic approximation algorithm for multidimensional case. In this generalization, the step incr...
In nonparametric classification and regression problems, support vector machines (SVMs) attract much attention in theoretical and in applied statistics. In an abstract sense, SVMs can be seen as regu...
The paper deals with the analysis of some natiual symmetries of one- and multidimensional problems of testing normality. Some grotips of transformations are coilsidered and their maximal invariants...
Asymptotic multivariate normality for the subseries values of a general statistic form a stationary sequence - with applications to nonparametric confidence intervals。
Let F be a non-lattice distribution function which lies in the domain of attraction of a normal distribution. Exact uniform convergence rates are obtained for the convergence of the normalized parti...
Wc mnf;i&r the paablem of density estimation for m a one-sided linear prosees X, = zt _ , a, Z, , with i.id square iategra- Me kovatims - We prove that under weak contritions on (ai)&, which imply ...
We propose a new test for multivariate normality based on the empirical characteristic function. We show that the test is afine invariant and consistent against every non-normal alternative. The te...

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