Announcement
Another Look at the Naive Estimator in a Regression Model.
Aplicaciones de los teoremas de separación para valores singulares de matrices al análisis de la redundancia.
El análisis de la redundancia constituye una alternativa al análisis de la correlación canónica en el estudio de la relación entre dos grupos de variables.La utilización de normas invariantes por matrices unitarias permite generalizar la definición de índice de la redundancia. Con los teoremas de separación para valores singulares de matrices se obtienen caracterizaciones similares del análisis de la redundancia y del análisis de la correlación canónica.En el problema de la regresión reduciendo...
Application de l'analyse de données à l'élaboration de mini-sondages d'opinion
Application d'un modèle d'association à l'analyse d'une table de taux
Application of discriminant, classification tree and neural network analysis to differentiate between potential glaucoma suspects with and without visual field defects.
Application of the Rasch model in categorical pedigree analysis using MCEM: I binary data
An extension of the Rasch model with correlated latent variables is proposed to model correlated binary data within families. The latent variables have the classical correlation structure of Fisher (1918) and the model parameters thus have genetic interpretations. The proposed model is fitted to data using a hybrid of the Metropolis-Hastings algorithm and the MCEM modification of the EM-algorithm and is illustrated using genotype-phenotype data on a psychological subtest in families where some members...
Applications of monotonic dependence functions: descriptive aspects
Applications of the theory of partially ordered sets to cluster analysis
Apport de l'analyse factorielle à l'étude d'un processus
Approaches to Identification of Linear Relations from Compound Noisy and Noise-Free Data
Approximate polynomial expansion for joint density
Let (X,Y) be a random vector with joint probability measure σ and with margins μ and ν. Let and be two bases of complete orthonormal polynomials with respect to μ and ν, respectively. Under integrability conditions we have the following polynomial expansion: . In this paper we consider the problem of changing the margin μ into μ̃ in this expansion. That is the case when μ is the true (or estimated) margin and μ̃ is its approximation. It is shown that a new joint probability with new margins...
Approximation des dissimilarités par des arbres additifs
Approximation d'une préordonnance par une partition
Aspects of analysis of multivariate failure time data.
Multivariate failure time data arise in various forms including recurrent event data when individuals are followed to observe the sequence of occurrences of a certain type of event; correlated failure time when an individual is followed for the occurrence of two or more types of events for which the individual is simultaneously at risk, or when distinct individuals have depending event times; or more complicated multistate processes where individuals may move among a number of discrete states over...
Association entre variables qualitatives ordinales «nettes» ou «floues»
Asymmetric semilinear copulas
We complement the recently introduced classes of lower and upper semilinear copulas by two new classes, called vertical and horizontal semilinear copulas, and characterize the corresponding class of diagonals. The new copulas are in essence asymmetric, with maximum asymmetry given by . The only symmetric members turn out to be also lower and upper semilinear copulas, namely convex sums of and .
Asymptotic behaviour of a BIPF algorithm with an improper target
The BIPF algorithm is a Markovian algorithm with the purpose of simulating certain probability distributions supported by contingency tables belonging to hierarchical log-linear models. The updating steps of the algorithm depend only on the required expected marginal tables over the maximal terms of the hierarchical model. Usually these tables are marginals of a positive joint table, in which case it is well known that the algorithm is a blocking Gibbs Sampler. But the algorithm makes sense even...
Asymptotic behaviour of the quadratic measure of deviation of multivariate density estimates
Asymptotic covariances for the generalized gamma distribution
The five-parameter generalized gamma distribution is one of the most flexible distributions in statistics. In this note, for the first time, we provide asymptotic covariances for the parameters using both the method of maximum likelihood and the method of moments.