Nonparametric estimation of location parameter after a preliminary test on regression in the multivariate case

For a simple multivariate regression model, nonparametric estimation of the (vector of) intercept following a preliminary test on the regression vector is considered. Along with the asymptotic distribution of these estimators, their asymptotic bias and dispersion matrices are studied and allied efficiency results are presented.     

On the monotonicity of the power functions of tests based on traces of multivariate beta matrices

It is shown that for the MANOVA problem the power function of the test based on the trace of a multivariate beta matrix is monotonically increasing in each noncentrality parameter provided that the cutoff point is not too large. This result is also true for the problem of testing independence of two sets of variates.     

On the robustness of least squares procedures in regression models

The criterion robustness of the standard likelihood ratio test (LRT) under the multivariate normal regression model and also the inference robustness of the same test under the univariate set up are established for certain nonnormal distributions of errors. Restricting attention to the normal distribution of errors in the context of univariate regression models, conditions on the design matrix are established under which the usual LRT of a linear hypothesis (under homoscedasticity of errors) remains valid if the errors have an intraclass covariance structure. The conditions hold in the case of some standard designs. The relevance of C. R. Rao's (1967 In Proceedings Fifth Berkeley Symposium on Math. Stat. and Prob., Vol. 1, pp. 355–372) and G. Zyskind's (1967, Ann. Math. Statist.38 1092–1110) conditions in this context is discussed.     

Trust-region algorithms for derivative-free optimization and nonlinear bilevel programming

We briefly describe the contents of the authors PhD thesis (see Colson 2003) discussed on July 2003 at the University of Namur (Belgium) and supervised by Philippe L. Toint. The contributions presented in this thesis are the development of trust-region methods for solving two particular classes of mathematical programs, namely derivative-free optimization (DFO) problems and nonlinear bilevel programming problems. The thesis is written in English and is available via the author.Received: July 2003, AMS classification: 65D05, 90C30, 90C56, 90C59     

Estimation of the Multivariate Normal Precision Matrix under the Entropy Loss

Let X ₁, , X _n (n > p) be a random sample from multivariate normal distribution N _p (, ), where R ^p and is a positive definite matrix, both and being unknown. We consider the problem of estimating the precision matrix ^–1. In this paper it is shown that for the entropy loss, the best lower-triangular affine equivariant minimax estimator of ^–1 is inadmissible and an improved estimator is explicitly constructed. Note that our improved estimator is obtained from the class of lower-triangular scale equivariant estimators.     

Evidence of red cell alignment in the magnetic field of an NMR spectrometer based on the diffusion tensor of water

The alignment of human erythrocytes in aqueous suspensions in the magnetic field B(0) (called the z-direction) of an NMR spectrometer was shown by calculating the diffusion tensor for water in the sample. The diffusion was measured using a pulsed-field-gradient spin-echo NMR method. The extent of diffusion anisotropy for water was exemplified by the values of the apparent diffusion coefficients with erythrocytes of normal shape and volume: for a typical experiment the values for the x-, y-, and z-directions were (6.88 +/- 0.17) x 10(-10), (7.07 +/- 0.17) x 10(-10), and (10.20 +/- 0.17) x 10(-10) m(2) s(-1), respectively. Cells in hypo- and hyperosmotic media were also studied and they too showed the anisotropy of the apparent diffusion coefficients but the extents were different. A new method of data analysis was developed using the Standard Add-On Packages in a Mathematica program. The experimental findings support evidence of erythrocyte alignment that was previously obtained with a high-field-gradient q-space method.     

基于多元局部多项式方法的混沌时间序列预测

根据Takens定理，把混沌时间序列构造为一组序列对，然后用多元局部多项式方法来预测其序列.这种核估计方法可以结合局域法与全局法的优点，使得预测的精度更高.仿真结果表明，该方法非常有效.     

Asymptotic formulae for multivariate Kantorovich type generalized sampling series

In this paper an asymptotic formula of Voronovskaja type for a multivariate extension of the Kantorovich generalized sampling series is given. Moreover a quantitative version in terms of some moduli of smoothness is established. Finally some particular examples of kernels are discussed, as the Bochner-Riesz kernel and the multivariate splines.     

Theory of optimal consumption and portfolio selection under a Capital-at-Risk (CaR) and a Value-at-Risk (VaR) constraint

The solution to the optimal portfolio selection and consumptionrule subject to Capital-at-Risk and Value-at-Risk constraintsis derived via the use of stochastic dynamic programming.     

The multivariate N-Component resolution problem with minimum assumptions

The present state of the minimum assumption multivariate component resolution theory is outlined. Some new developments are presented: limiting function domains; the analytical expression for the limiting function; efficient algorithms for defining the FIRPOL and INNPOL hyperpolyhedrons. A very low resolution data set is analyzed.