A nonparametric method of regression analysis from censored data
A Note on a Sequence of Quadratic Forms
A note on Ahlers and Lewis' representation of the best linear unbiased estimator in the general Gauss-Markoff model
A note on asymptotic linearity of -statistics in nonlinear models
A note on control of the false discovery proportion
We consider the problem of simultaneous testing of a finite number of null hypotheses , i=1,...,s. Starting from the classical paper of Lehmann (1957), it has become a very popular subject of research. In many applications, particularly in molecular biology (see e.g. Dudoit et al. (2003), Pollard et al. (2005)), the number s, i.e. the number of tested hypotheses, is large and the popular procedures that control the familywise error rate (FWERM) have small power. Therefore, we are concerned with...
A note on the existence of the maximum likelihood estimate in variance components models
In the paper, the problem of the existence of the maximum likelihood estimate and the REML estimate in the variance components model is considered. Errors in the proof of Theorem 3.1 in the article of Demidenko and Massam (Sankhyā 61, 1999), giving a necessary and sufficient condition for the existence of the maximum likelihood estimate in this model, are pointed out and corrected. A new proof of Theorem 3.4 in the Demidenko and Massam's article, concerning the existence of the REML estimate of...
A note on the rate of convergence of local polynomial estimators in regression models
Local polynomials are used to construct estimators for the value of the regression function and the values of the derivatives in a general class of nonparametric regression models. The covariables are allowed to be random or non-random. Only asymptotic conditions on the average distribution of the covariables are used as smoothness of the experimental design. This smoothness condition is discussed in detail. The optimal stochastic rate of convergence of the estimators is established. The results...
A note on the strong consistency of least squares estimates
The strong consistency of least squares estimates in multiples regression models with i.i.d. errors is obtained under assumptions on the design matrix and moment restrictions on the errors.
A novel fuzzy c-regression model algorithm using a new error measure and particle swarm optimization
This paper presents a new algorithm for fuzzy c-regression model clustering. The proposed methodology is based on adding a second regularization term in the objective function of a Fuzzy C-Regression Model (FCRM) clustering algorithm in order to take into account noisy data. In addition, a new error measure is used in the objective function of the FCRM algorithm, replacing the one used in this type of algorithm. Then, particle swarm optimization is employed to finally tune parameters of the obtained...
A present overview on functional data analysis.
A Probability Inequality for Ranges and its Application to Maximum Range Test Procedures.
A Problem in Least Squares.
A procedure for ε-comparison of means of two normal distributions
For two normal distributions N(μ₁,σ²) and N(μ₂,σ²) the problem is to decide whether |μ₁-μ₂|≤ ε for a given ε. Two decision rules are given: maximin and bayesian for σ² known and unknown.
À propos du théorème de Gauss-Markov
A regression characterization of inverse Gaussian distributions and application to EDF goodness-of-fit tests.
A review of generalized linear mixed models
A review of the results on the Stein approach for estimators improvement.
Since 1956, a large number of papers have been devoted to Stein's technique of obtaining improved estimators of parameters, for several statistical models. We give a brief review of these papers, emphasizing those aspects which are interesting from the point of view of the theory of unbiased estimation.
A simplex design for gradient estimation in quadratic regression
A simplified treatment of the restricted analysis of a slightly disproportionate factorial experiment.
This paper considers a procedure to obtain effect estimators in the least squares analysis of a slightly disproportionate factorial design when a sample survey is made of the results of an extensive experiment. Explicit formulae have been found for the restricted estimators and their variances, when the constraints normally imposed upon a proportional model are used. In addition, an approximate analysis of the original model is used to perform that estimation, and an approximate analysis of variance...
A square root filter for real time multivariate regression