Confidence band for regression line with exponential distribution of errors
Confidence regions in a multivariate regression model with constraints II
Confidence regions in nonlinear models with constraints
Confidence regions in nonlinear regression models
New curvature measures for nonlinear regression models are developed and methods of their computing are given. Using these measures, more accurate confidence regions for parameters than those based on linear or quadratic approximations are obtained.
Consistency in the p-th mean of the least Squares Estimators in Linear Models
Consistency of an estimate in linear regression with non-negative errors
Consistency of least squares estimates in a system of linear correlation models [Book]
Consistency of linear and quadratic least squares estimators in regression models with covariance stationary errors
The least squres invariant quadratic estimator of an unknown covariance function of a stochastic process is defined and a sufficient condition for consistency of this estimator is derived. The mean value of the observed process is assumed to fulfil a linear regresion model. A sufficient condition for consistency of the least squares estimator of the regression parameters is derived, too.
Consistency of the least weighted squares under heteroscedasticity
A robust version of the Ordinary Least Squares accommodating the idea of weighting the order statistics of the squared residuals (rather than directly the squares of residuals) is recalled and its properties are studied. The existence of solution of the corresponding extremal problem and the consistency under heteroscedasticity is proved.
Consistency of the LSE in Linear regression with stationary noise
We obtain conditions for L₂ and strong consistency of the least square estimators of the coefficients in a multi-linear regression model with a stationary random noise. For given non-random regressors, we obtain conditions which ensure L₂-consistency for all wide sense stationary noise sequences with spectral measure in a given class. The condition for the class of all noises with continuous (i.e., atomless) spectral measures yields also -consistency when the noise is strict sense stationary with...
Consistent Estimation of a Regression with Errors in the Variables.
Contribuciones a la generalización del problema de compensación por grupos de Helmert-Pranis Pranievich.
The paper presents in a generalized form the problem of the geodetic network adjustment by the Helmert-Pranis Pranievich groups method (groups with junction points included or not). The adjustment problem, as well as the cofactor matrix derivation for the partial-independent and linkage unknowns, was completely formulated by transformed weight matrix definition and usage. A complete sequence of the computing stages for the geodetic networks divided into groups without junction points was given for...
Corrections of estimators in linearized models
Covariance matrix elements estimation: special linear model without and with repeated measurement
Covariance Structure of Principal Components for Three-Part Compositional Data
Statistical analysis of compositional data, multivariate observations carrying only relative information (proportions, percentages), should be performed only in orthonormal coordinates with respect to the Aitchison geometry on the simplex. In case of three-part compositions it is possible to decompose the covariance structure of the well-known principal components using variances of log-ratios of the original parts. They seem to be helpful for the interpretation of these special orthonormal coordinates....
Criterion for an approximation of variance components in regression models