Erratum «Deux méthodes linéaires en statistique multidimensionnelle»
Estimación de registros desconocidos en series de datos.
Se dispone de dos o más series de datos, de las cuales al menos una no se conoce completamente. Se supone que las series se pueden modelizar con la hipótesis lineal; así como que existe alguna estructura de correlación entre ellas. Se desarrollan dos modelos para estimar los valores desconocidos de la(s) serie(s) de datos.
Estimation of parameters of mean and variance in two-stage linear models
The paper deals with the estimation of unknown vector parameter of mean and scalar parameters of variance as well in two-stage linear model, which is a special type of mixed linear model. The necessary and sufficient condition for the existence of uniformly best unbiased estimator of parameter of means is given. The explicite formulas for these estimators and for the estimators of the parameters of variance as well are derived.
Experience in computing optimal regression by branch and bound
Experiments with mixtures: An alternative to the {q, 3} and {q, 4} simplex-lattice designs
F and selective F tests with balanced cross-nesting and associated models
F tests and selective F tests for fixed effects part of balanced models with cross-nesting are derived. The effects of perturbations in the numerator and denominator of the F statistics are considered.
F-tests for generalized linear hypotheses in subnormal models
When the measurement errors may be assumed to be normal and independent from what is measured a subnormal model may be used. We define a linear and generalized linear hypotheses for these models, and derive F-tests for them. These tests are shown to be UMP for linear hypotheses as well as strictly unbiased and strongly consistent for these hypotheses. It is also shown that the F-tests are invariant for regular transformations, possess structural stability and are almost strongly consistent for generalized...
Knowledge-based Green's kernel for support vector regression.
Likelihood and parametric heteroscedasticity in normal connected linear models
A linear model in which the mean vector and covariance matrix depend on the same parameters is connected. Limit results for these models are presented. The characteristic function of the gradient of the score is obtained for normal connected models, thus, enabling the study of maximum likelihood estimators. A special case with diagonal covariance matrix is studied.
Linear conform transformation: Errors in both coordinate systems
Linear conform transformation in the case of non-negligible errors in both coordinate systems is investigated. Estimation of transformation parameters and their statistical properties are described. Confidence ellipses of transformed nonidentical points and cross covariance matrices among them and identical points are determined. Some simulation for a verification of theoretical results are presented.
Linear-quadratic estimators in a special structure of the linear model
The paper deals with the linear model with uncorrelated observations. The dispersions of the values observed are linear-quadratic functions of the unknown parameters of the mean (measurements by devices of a given class of precision). Investigated are the locally best linear-quadratic unbiased estimators as improvements of locally best linear unbiased estimators in the case that the design matrix has none, one or two linearly dependent rows.
Minimum penalty estimate
Model Assisted Survey Sampling Strategy in Two Phases.
Multilinear Estimation of Skewness and Kurtosis in Linear Models.
Non-central generalized F distributions
The quotient of two linear combinations of independent chi-squares will have a generalized F distribution. Exact expressions for these distributions when the chi-square are central and those in the numerator or in the denominator have even degrees of freedom were given in Fonseca et al. (2002). These expressions are now extended for non-central chi-squares. The case of random non-centrality parameters is also considered.
Numerical experiments with least squares spline estimators in a parametric regression model.
On the General Problem of Adjustment of Measured Values
One of the calibration problems
Optimale Versuchspläne bei zweifach klassifizierten Beobachtungsmodellen
Pattern-mixture models