Modèle log-linéaire et modèle de Cox dans l'analyse d'une table de contingence
Modeling abilities in 3-IRT models.
Modeling and forecasting the peak flows of a river.
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 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.
Moindres carrés pondérés et poursuite
Monotonicity properties of statistical procedures for an increasing number of observations or a decreasing number of parameters, especially Anova procedures
MSE-Improvement of the Least Squares Estimator by Dropping Variables.
Multilinear Estimation of Skewness and Kurtosis in Linear Models.
Multistage regression model
Necessary and sufficient conditions are given under which the best linear unbiased estimator (BLUE) is identical with the BLUE ; are subvectors of the random vector in a general regression model , a vector of unknown parameters; the design matrix having a special so called multistage struture and the covariance matrix are given.
Multivariate models with constraints confidence regions
In multivariate linear statistical models with normally distributed observation matrix a structure of a covariance matrix plays an important role when confidence regions must be determined. In the paper it is assumed that the covariance matrix is a linear combination of known symmetric and positive semidefinite matrices and unknown parameters (variance components) which are unbiasedly estimable. Then insensitivity regions are found for them which enables us to decide whether plug-in approach can...
Multivariate Multistage Methodologies for Simultaneous All Pairwise Comparisons.
Multivariate regression model with constraints
Multivariate statistical models; solvability of basic problems
Multivariate models frequently used in many branches of science have relatively large number of different structures. Sometimes the regularity condition which enable us to solve statistical problems are not satisfied and it is reasonable to recognize it in advance. In the paper the model without constraints on parameters is analyzed only, since the greatness of the class of such problems in general is out of the size of the paper.