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Let us have a system of variables, among which there are complicated dependences. Assuming reflexivity and transitivity of the relation " depends on ", a simple algorithm is proposed which produces all dependences in an optimized way, without losing information.
En el presente artículo se recogen los resultados de una investigación llevada a cabo sobre el comportamiento de pretest de heterocedasticidad. Con este fin se ha diseñado un experimento Monte Carlo, introduciendo como proceso generador de datos un modelo con tres supuestos sobre la estructura de la varianza del error y con distintos niveles de heteroscedasticidad para cada uno de ellos. Asimismo, se analiza la potencia de los diferentes contrastes de heterocedasticidad bajo los distintos supuestos...
Let us consider the linear model covering the one-way classification as a special casse. In the paper the relationship between testing of some linear hypothesis and estimating of parameters in the linear model by common software packages is examined.
Compositional data, multivariate observations that hold only relative information, need a special treatment while performing statistical analysis, with respect to the simplex as their sample space ([Aitchison, J.: The Statistical Analysis of Compositional Data. Chapman and Hall, London, 1986.], [Aitchison, J., Greenacre, M.: Biplots of compositional data. Applied Statistics 51 (2002), 375–392.], [Buccianti, A., Mateu-Figueras, G., Pawlowsky-Glahn, V. (eds): Compositional data analysis in the geosciences:...
Continuando el desarrollo del modelo lineal sobre dos variables dummy difusas, encontramos expresiones para las descomposiciones clásicas en sumas de cuadrados y estudiamos sus distribuciones bajo hipótesis de normalidad. Damos una interpretación geométrica del ajuste cuando las variables numéricas explicativas se ven sometidas a una codificación difusa de tipo semilineal y contrastamos en estos casos la mejora de este nuevo modelo respecto de la regresión sobre las variables originales. Concluimos...
En el modelo de regresión lineal y = E(Y/X = x) = θx, donde (X,Y) es un vector aleatorio bidimensional, del que se dispone de una muestra {(X1, Y1), ..., (Xn, Yn)}, se han introducido recientemente una clase general de estimadores para θ definida como aquellos valores que minimizan el funcional:ψ(θ) = ∫ (αn(x) - θx)2 dΩn(x)donde αn es un estimador no paramétrico del tipo núcleo o histograma para α(x) = E(Y/X = x) y Ωn una función de ponderación.En este trabajo se extiende tal estudio cuando inicialmente...
Given a base design with quantitative factors and a primary linear regression to each of the treatments, we may adjust secondary regressions of linear combinations of the adjusted coefficients on the primary regressions on the factor levels, thus obtaining a biregressional model.
A biregressional design was established for a set of treatments, defined from quantitative factors and a linear regression in the same variables. Afterwards the action of the regression coefficients...
Many data sets analyzed in human and social sciences have a multilevel or hierarchical structure. By hierarchy we mean that units of a certain level (also referred micro units) are grouped into, or nested within, higher level (or macro) units. In these cases, the units within a cluster tend to be more different than units from other clusters, i.e., they are correlated. Thus, unlike in the classical setting where there exists a single source of variation between observational units, the heterogeneity...
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