A chain regression estimator in two phase sampling using multi-auxiliary information.
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A Characterization of the Normal Distribution by Sufficiency of the Least Squares Estimation.
W. Fieger, W. Bischoff, H. Cremers (1987)
Metrika
A choice of criterion parameters in a linearization of regression models.
Jenčová, A. (1995)
Acta Mathematica Universitatis Comenianae. New Series
A comparison of cointegration tests
Petr Mariel (1996)
Applications of Mathematics
In this paper some of the cointegration tests applied to a single equation are compared. Many of the existent cointegration tests are simply extensions of the unit root tests applied to the residuals of the cointegrating regression and the habitual is no cointegration. However, some non residual-based tests and some tests of the opposite null hypothesis have recently appeared in literature. Monte Carlo simulations have been used for the power comparison of the nine selected tests (, , , ,...
A Dual Approach for Matrix-Derivatives.
W. Polasek (1985)
Metrika
A minimax property of translation invariant estimators for variance components
J. Kleffe (1979)
Applicationes Mathematicae
A New Interpretation of Optimality for E-Optimal Designs in linear Regression Models.
Holger Dette (1993)
Metrika
A new stochastic restricted biased estimator under heteroscedastic or correlated error
Mustafa Ismaeel Alheety (2011)
ESAIM: Probability and Statistics
In this paper, under the linear regression model with heteroscedastic and/or correlated errors when the stochastic linear restrictions on the parameter vector are assumed to be held, a generalization of the ordinary mixed estimator (GOME), ordinary ridge regression estimator (GORR) and Generalized least squares estimator (GLSE) is proposed. The performance of this new estimator against GOME, GORR, GLS and the stochastic restricted Liu estimator (SRLE) [Yang and Xu, Statist. Papers 50 (2007) 639–647]...
A new stochastic restricted biased estimator under heteroscedastic or correlated error
Mustafa Ismaeel Alheety (2011)
ESAIM: Probability and Statistics
In this paper, under the linear regression model with heteroscedastic and/or correlated errors when the stochastic linear restrictions on the parameter vector are assumed to be held, a generalization of the ordinary mixed estimator (GOME), ordinary ridge regression estimator (GORR) and Generalized least squares estimator (GLSE) is proposed. The performance of this new estimator against GOME, GORR, GLS and the stochastic restricted Liu estimator (SRLE) [Yang and Xu, Statist. Papers50 (2007) 639–647]...
A nonparametric method of regression analysis from censored data
Petr Volf (1988)
Kybernetika
A Note on a Sequence of Quadratic Forms
Demetrios G. Kaffes (1987)
Δελτίο της Ελληνικής Μαθηματικής Εταιρίας
A note on Ahlers and Lewis' representation of the best linear unbiased estimator in the general Gauss-Markoff model
Jerzy Baksalary, Radosław Kala (1980)
Banach Center Publications
A note on the existence of the maximum likelihood estimate in variance components models
Mariusz Grządziel, Andrzej Michalski (2014)
Discussiones Mathematicae Probability and Statistics
In the paper, the problem of the existence of the maximum likelihood estimate and the REML estimate in the variance components model is considered. Errors in the proof of Theorem 3.1 in the article of Demidenko and Massam (Sankhyā 61, 1999), giving a necessary and sufficient condition for the existence of the maximum likelihood estimate in this model, are pointed out and corrected. A new proof of Theorem 3.4 in the Demidenko and Massam's article, concerning the existence of the REML estimate of...
A note on the strong consistency of least squares estimates
Joǎo Lita da Silva (2009)
Discussiones Mathematicae Probability and Statistics
The strong consistency of least squares estimates in multiples regression models with i.i.d. errors is obtained under assumptions on the design matrix and moment restrictions on the errors.
A present overview on functional data analysis.
M. Febrero (2008)
Boletín de Estadística e Investigación Operativa. BEIO
A Problem in Least Squares.
Mansfield Merriman (1891/1892)
Bulletin of the New York Mathematical Society
À propos du théorème de Gauss-Markov
J.-L. Philoche (1971)
Annales de l'I.H.P. Probabilités et statistiques
A review of generalized linear mixed models
Geert Molenberghs, Didier Renard, Geert Verbeke (2002)
Journal de la société française de statistique
A simplex design for gradient estimation in quadratic regression
R. Zieliński (1973)
Applicationes Mathematicae
A square root filter for real time multivariate regression
Václav Peterka (1975)
Kybernetika
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