Results 231 to 240 of about 7,710 (298)

On the Use of Auxiliary Variables in Multilevel Regression and Poststratification. [PDF]

Stat Sci
Si Y.
europepmc   +1 more source

How and why to follow best practices for testing mediation models with missing data. [PDF]

Int J Psychol
Schoemann AM, Moore EWG, Yagiz G.
europepmc   +1 more source

Best linear unbiased estimators for properties of straight lines

IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986
Dorst, L., Smeulders, A.W.M.
openaire   +2 more sources

A bound for the Euclidean norm of the difference between the best linear unbiased estimator and a linear unbiased estimator

Journal of Geodesy, 2002
A bound is established for the Euclidean norm of the difference between the best linear unbiased estimator and any linear unbiased estimator in the general linear model. The bound involves the spectral norm of the difference between the dispersion matrices of the two estimators, and the residual sum of squares, all evaluated at the assumed model, but ...
Jaakko Mäkinen
openaire   +3 more sources

A Characterization of Best Linear Unbiased Estimators in the General Linear Model

, 1980
A characterization of best linear unbiased estimators is given in the case of the general linear model. In addition necessary and sufficient conditions are derived for a given estimable function to have a best linear unbiased estimator. In particular models for which each estimable function has a best linear unbiased estimator are characterized.
Roman Zmyślony
openaire   +3 more sources

Some efficiency properties of best linear unbiased estimators

Journal of Statistical Planning and Inference, 2003
In this paper, we show that the best linear unbiased estimators of the location and scale parameters of a location-scale parameter distribution based on a general Type-II censored sample are in fact trace-efficient linear unbiased estimators as well as determinant-efficient linear unbiased estimators.
Calyampudi Radhakrishna Rao, Narayanaswamy Balakrishnan   +1 more
openaire   +3 more sources

The Equality of the Ordinary Least Squares Estimator and the Best Linear Unbiased Estimator

The American Statistician, 1989
Abstract It is well known that the ordinary least squares estimator of Xβ in the general linear model E y = Xβ, cov y = σ2 V, can be the best linear unbiased estimator even if V is not a multiple of the identity matrix. This article presents, in a historical perspective, the development of the several conditions for the ordinary least squares estimator
George P. H. Styan, Simo Puntanen
openaire   +3 more sources

Two matrix-based proofs that the linear estimator Gy is the best linear unbiased estimator

Journal of Statistical Planning and Inference, 2000
Abstract We offer two matrix-based proofs for the well-known result that the two conditions GX=X and GVQ=0 are necessary and sufficient for Gy to be the traditional best linear unbiased estimator (BLUE) of Xβ in the Gauss–Markov linear model {y,Xβ,V}, where y is an observable random vector with expectation vector E (y)=Xβ and dispersion matrix
Simo Puntanen, George P. H. Styan, Hans Joachim Werner   +2 more
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On Multilevel Best Linear Unbiased Estimators

SIAM/ASA Journal on Uncertainty Quantification, 2020
We present a general variance reduction technique for the estimation of the expectation of a scalar-valued quantity of interest associated with a family of model evaluations.
Daniel Schaden, Elisabeth Ullmann
openaire   +2 more sources