Faktorové experimenty v průmyslovém výzkumu
Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA, which is based on the estimation of the sample mean and covariance matrix of the data, is very sensitive to outliers in the training data set. Usually robust principal component analysis is applied to remove the effect of outliers on the PCA model. In this paper, a fast two-step algorithm is proposed. First, the objective was to find an accurate estimate of the covariance matrix of...
El análisis de correspondencias múltiples (ACM) estudia la relación entre varias variables cualitativas definidas sobre una misma población. Sin embargo, una de las principales fuentes de información son las encuestas donde es frecuente encontrar cierto número de datos ausentes y de preguntas condicionadas. Escofier (Escofier 1981) propone analizar la tabla disyuntiva incompleta sustituyendo la marginal real de la tabla sobre los individuos por una marginal impuesta constante. El análisis de la...
Son casi innumerables las reflexiones que se han hecho en el campo de la metodología de las ciencias sociales, sobre la dicotomía, real o inexistente, entre las perspectivas de análisis cuantitativo y cualitativo, mientras que han sido menos abundantes los trabajos teóricos, aunque van siendo más abundantes los empíricos, que han tratado de compatibilizar y/o complementar ambas perspectivas. En muchos casos los trabajos cualitativos cubren solamente los primeros pasos de la investigación social,...
This paper gives a generalization of results presented by ten Berge, Krijnen,Wansbeek & Shapiro. They examined procedures and results as proposed by Anderson & Rubin, McDonald, Green and Krijnen, Wansbeek & ten Berge.We shall consider the same matter, under weaker rank assumptions. We allow some moments, namely the variance Ω of the observable scores vector and that of the unique factors, Ψ, to be singular. We require T' Ψ T > 0, where T Λ T' is a Schur decomposition of Ω. As...
We consider representations of a joint distribution law of a family of categorical random variables (i.e., a multivariate categorical variable) as a mixture of independent distribution laws (i.e. distribution laws according to which random variables are mutually independent). For infinite families of random variables, we describe a class of mixtures with identifiable mixing measure. This class is interesting from a practical point of view as well, as its structure clarifies principles of selecting...
In this paper we deepen the study of the nonlinear principal components introduced by Salinelli in 1998, referring to a real random variable. New insights on their probabilistic and statistical meaning are given with some properties. An estimation procedure based on spline functions, adapting to a statistical framework the classical Rayleigh–Ritz method, is introduced. Asymptotic properties of the estimator are proved, providing an upper bound for the rate of convergence under suitable mild conditions....