Minimum Variance Unbiased Estimation of Multivariate Modified Power Series Distribution.
Minimum Variance Unbiased Estimation of the Parameters of the Pareto Distribution.
Model and variable selection procedures for semiparametric time series regression.
Modelización de datos longitudinales con estructuras de covarianza no estacionarias: modelos de coeficientes aleatorios frente a modelos alternativos.
Un tema que ha suscitado el interés de los investigadores en datos longitudinales durante las dos últimas décadas, ha sido el desarrollo y uso de modelos paramétricos explícitos para la estructura de covarianza de los datos. Sin embargo, el análisis de estructuras de covarianza no estacionarias en el contexto de datos longitudinales no se ha realizado de forma detallada principalmente debido a que las distintas aplicaciones no hacían necesario su uso. Muchos son los modelos propuestos recientemente,...
Modified Integer-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.
Modified power divergence estimators in normal models – simulation and comparative study
Point estimators based on minimization of information-theoretic divergences between empirical and hypothetical distribution induce a problem when working with continuous families which are measure-theoretically orthogonal with the family of empirical distributions. In this case, the -divergence is always equal to its upper bound, and the minimum -divergence estimates are trivial. Broniatowski and Vajda [3] proposed several modifications of the minimum divergence rule to provide a solution to the...
Modified Weibull distribution.
Monte Carlo detection of outliers of data and cryptographic applications.
Motivation, existence and equivariance of -estimators
Necessary and Sufficient Conditions for Consistency of Generalized M-Estimates.
New estimates and tests of independence in semiparametric copula models
We introduce new estimates and tests of independence in copula models with unknown margins using -divergences and the duality technique. The asymptotic laws of the estimates and the test statistics are established both when the parameter is an interior or a boundary value of the parameter space. Simulation results show that the choice of -divergence has good properties in terms of efficiency-robustness.
New models in durability tool-testing: pseudo-Weibull distribution
Nonlinear error propagation law
The error propagation law is investigated in the case of a nonlinear function of measured data with non-negligible uncertainty.
Nonsensitiveness regions in universal models
Note on dispersion of .
Note on Dispersion of Xalpha
Note on the estimation of parameters of the mean and the variance in -stage linear models
The paper deals with the estimation of the unknown vector parameter of the mean and the parameters of the variance in the general -stage linear model. Necessary and sufficient conditions for the existence of the uniformly minimum variance unbiased estimator (UMVUE) of the mean-parameter under the condition of normality are given. The commonly used least squares estimators are used to derive the expressions of UMVUE-s in a simple form.
Note on the truncated Rayleigh variate
Note on unbiased estimability of the larger of two mean values
An unbiased estimator of the larger of two mean values is constructed provided that the number of observations is random.