Editorial to the special issue on “Random Variables, Joint Distribution Functions, and Copulas”
Efecto de un proceso de poda en algunos coeficientes de asociación derivados del estadístico χ2.
Efecto del número de indicadores por factor sobre la identificación y estimación en modelos aditivos de análisis factorial confirmatorio.
La matriz multirrasgo-multimétodo (MRMM) es un diseño de investigación de larga tradición en Psicología. Las técnicas de análisis de datos adecuadas para una correcta extracción de conclusiones han estado sujetas a controversia. Parece, no obstante, que diversos modelos de análisis factorial confirmatorio resultan muy adecuados. De entre los diversos modelos, dos de ellos han recibido gran atención, el modelo completo, que apareció primero en la literatura, y el de unicidades correlacionadas, que...
Effect of choice of dissimilarity measure on classification efficiency with nearest neighbor method
In this paper we will precisely analyze the nearest neighbor method for different dissimilarity measures, classical and weighed, for which methods of distinguishing were worked out. We will propose looking for weights in the space of discriminant coordinates. Experimental results based on a number of real data sets are presented and analyzed to illustrate the benefits of the proposed methods. As classical dissimilarity measures we will use the Euclidean metric, Manhattan and post office metric....
Effect of prior probabilities on the classificatory performance of parametric and mathematical programming approaches to the two-group discriminant problem.
Effet des erreurs de mesure sur l'évaluation de l'efficacité d'un traitement
L’effet d’un traitement sur une compétence peut être exprimé par le coefficient de régression partiel avec contrôle de la compétence initiale . Quand et sont mesurées avec erreurs par et , cet effet se manifeste par le coefficient dans la régression de sur et . Le biais entre et est explicité, discuté et montré systématique si et sont corrélés. L’importance de bien spécifier le modèle, dont une condition nécessaire et suffisante d’identification est donnée, est mise en...
Eigenanalysis and metric multidimensional scaling on hierarchical structures.
The known hierarchical clustering scheme is equivalent to the concept of ultrametric distance. Every distance can be represented in a spatial model using multidimensional scaling. We relate both classes of representations of proximity data in an algebraic way, obtaining some results and relations on clusters and the eigenvalues of the inner product matrix for an ultrametric distance. Principal coordinate analysis on an ultrametric distance gives two classes of independent coordinates, describing...
El sesgo condicionado en el análisis de influencia: una revisión.
El sesgo condicionado se ha propuesto como diagnóstico de influencia en distintos modelos y técnicas estadísticas. Tratando de recoger una visión global de la utilidad del concepto, en este trabajo se hace una revisión general del mismo relacionándolo con la curva de sensibilidad y la curva de influencia muestral. Además, se señalan posibles líneas de trabajo que permitirán abordar el análisis de la influencia a través de este enfoque en una gran variedad de técnicas estadísticas.
Élaboration et évaluation d'un indice d'implication pour des données binaires. I
Élaboration et évaluation d'un indice d'implication pour des données binaires. 2
Eliminating transformations for nuisance parameters in linear regression models with type I constraints
The linear regression model in which the vector of the first order parameter is divided into two parts: to the vector of the useful parameters and to the vector of the nuisance parameters is considered. The type I constraints are given on the useful parameters. We examine eliminating transformations which eliminate the nuisance parameters without loss of information on the useful parameters.
Eliminating transformations for nuisance parameters in linear model
Elimination of bias for general measures of associations [Abstract of thesis]
Elliptische Streuflächen ebener Punkthaufen.
Empirical significance test of the goodness-of-fit for some pyramidal clustering procedures.
Through a series of simulation tests by Monte Carlo methods, some aspects relating to the inference concerning pyramidal trees built by the maximum and minimum methods are considered. In this sense, the quantiles of the γ-Goodman-Kruskal statistic allow us to tabulate a significance test of the goodness-of-fit of a pyramidal clustering procedure. On the other side, the pyramidal method of maximum is observed to be clearly better (more efficient) than that of the minimum in terms of the expected...
Employing different loss functions for the classification of images via supervised learning
Supervised learning methods are powerful techniques to learn a function from a given set of labeled data, the so-called training data. In this paper the support vector machines approach is applied to an image classification task. Starting with the corresponding Tikhonov regularization problem, reformulated as a convex optimization problem, we introduce a conjugate dual problem to it and prove that, whenever strong duality holds, the function to be learned can be expressed via the dual optimal solutions....
Equivalence Between Tie-Corrected Spearman Test and a Chi-Square Test in a Fourfold Contingency Table.
Equivalence of compositional expressions and independence relations in compositional models
We generalize Jiroušek’s (right) composition operator in such a way that it can be applied to distribution functions with values in a “semifield“, and introduce (parenthesized) compositional expressions, which in some sense generalize Jiroušek’s “generating sequences” of compositional models. We say that two compositional expressions are equivalent if their evaluations always produce the same results whenever they are defined. Our first result is that a set system is star-like with centre if...
Erratum «Deux méthodes linéaires en statistique multidimensionnelle»
Estimación de correlaciones utilizando envolturas convexas.
En el presente trabajo se realiza un estudio de la envoltura convexa de una muestra normal bivariante, analizando la distribución de la pendiente de sus aristas. En base a ello se propone un estimador del coeficiente de correlación de la población, investigando algunas propiedades del mismo.