Model selection via testing : an alternative to (penalized) maximum likelihood estimators
Modified minimax quadratic estimation of variance components
The paper deals with modified minimax quadratic estimation of variance and covariance components under full ellipsoidal restrictions. Based on the, so called, linear approach to estimation variance components, i. e. considering useful local transformation of the original model, we can directly adopt the results from the linear theory. Under normality assumption we can can derive the explicit form of the estimator which is formally find to be the Kuks–Olman type estimator.
M-Tests in Multivariate Models.
Multilevel correction adaptive finite element method for semilinear elliptic equation
A type of adaptive finite element method is presented for semilinear elliptic problems based on multilevel correction scheme. The main idea of the method is to transform the semilinear elliptic equation into a sequence of linearized boundary value problems on the adaptive partitions and some semilinear elliptic problems on very low dimensional finite element spaces. Hence, solving the semilinear elliptic problem can reach almost the same efficiency as the adaptive method for the associated boundary...
On a robust significance test for the Cox regression model
A robust significance testing method for the Cox regression model, based on a modified Wald test statistic, is discussed. Using Monte Carlo experiments the asymptotic behavior of the modified robust versions of the Wald statistic is compared with the standard significance test for the Cox model based on the log likelihood ratio test statistic.
On adaptive estimation in nonlinear regression
On consistent -estimators: Tuning constants, unimodality and breakdown
On -estimators viewed as -estimators
On robust estimation in the simplest exponential model
On second order efficiency of a robust test and approximations of its error probabilities
On the Choice of Support of Re-Descending ...-Functions in Linear Models with Asymmetric Error Distributions.
On the robustness of multiple regression coefficient estimators obtained by the p-point method
Optimal alternative robustness in Bayesian Decision Theory.
In Martin et al (2003), we suggested an approach to general robustness studies in Bayesian Decision Theory and Inference, based on ε-contamination neighborhoods. In this note, we generalise the results considering neighborhoods based on norms, specifically, the supremum norm for utilities and the total variation norm for probability distributions. We provide tools to detect changes in preferences between alternatives under perturbations of the prior and/or the utility and the most sensitive direction....
Optimal mean-variance robust hedging under asset price model misspecification.
Optimality of the least weighted squares estimator
The present paper deals with least weighted squares estimator which is a robust estimator and it generalizes classical least trimmed squares. We will prove -consistency and asymptotic normality for any sequence of roots of normal equation for location model. The influence function for general case is calculated. Finally optimality of this estimator is discussed and formula for most B-robust and most V-robust weights is derived.
Outliers in models with constraints
Outliers in univariate and multivariate regression models with constraints are under consideration. The covariance matrix is assumed either to be known or to be known only partially.
Output feedback regulation for large-scale uncertain nonlinear systems with time delays
This paper is concerned with the problem of global state regulation by output feedback for large-scale uncertain nonlinear systems with time delays in the states and inputs. The systems are assumed to be bounded by a more general form than a class of feedforward systems satisfying a linear growth condition in the unmeasurable states multiplying by unknown growth rates and continuous functions of the inputs or delayed inputs. Using the dynamic gain scaling technique and choosing the appropriate Lyapunov-Krasovskii...
Partial review of adaptive procedures
Periodic transformations of the sample average reciprocal value
Permanents, order statistics, outliers, and robustness.
In this paper, we consider order statistics and outlier models, and focus primarily on multiple-outlier models and associated robustness issues. We first synthesise recent developments on order statistics arising from independent and non-identically distributed random variables based primarily on the theory of permanents. We then highlight various applications of these results in evaluating the robustness properties of several linear estimators when multiple outliers are possibly present in the...