Results 281 to 290 of about 2,457,284 (319)

An Improved Estimator of the Variance of the Regression Estimator

Biometrical Journal, 1999
Summary: The problem of estimation of variance of the general linear regression estimator has been considered. It has been shown that the first order calibration approach is a special case of the class of estimators proposed by \textit{L.-Y. Deng} and \textit{C. F. J. Wu} [J. Am. Stat. Assoc. 82, 568-576 (1987; Zbl 0629.62016)].
Singh, Sarjinder, Horn, Stephen
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Robust Estimators for Estimating Discontinuous Functions

Metrika, 2002
We study the asymptotic behavior of a wide class of kernel estimators for estimating an unknown regression function. In particular we derive the asymptotic behavior at discontinuity points of the regression function. It turns out that some kernel estimators based on outlier robust estimators are consistent at jumps.
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ESTIMABILITY AND ESTIMATION IN CASE-REFERENT STUDIES

American Journal of Epidemiology, 1976
The concepts that case-referent studies provide for the estimation of "relative risk" only if the illness is "rare", and that the rates and risks themselves are inestimable, are overly superficial and restrictve. The ratio of incidence densities (forces of morbidity)-and thereby the instantaneous risk-ratio-is estimable without any rarity-assumption ...
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Robust Estimation Through Estimating Equations

Biometrika, 1984
The paper deals with the choice of parameter definition. It develops the concepts of parameter defining function and effective parameter. It also provides theory and techniques for choosing from a given set of robust parameters the one that can most efficiently be estimated. This theory is applied to location parameters.
Godambe, V. P., Thompson, M. E.
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Estimating the Loss of Estimators of a Binomial Parameter

Biometrika, 1988
A loss function is introduced, which combines the estimation error of a statistical procedure with a measure of its accuracy. The properties of this loss function are illustrated by the estimator of a binomial parameter. The choice of a conjugate prior distribution is discussed from this point of view.
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Discussion of parameter estimation in biological modelling: Algorithms for estimation and evaluation of the estimates

Journal of Mathematical Biology, 1975
This paper is concerned with the estimation of parameters when mathematical models are fitted to data. Two new algorithms are presented. The first is fast (economical in computation time), requires no initial estimates, but is not so accurate. The second requires more computation time, and fairly accurate initial estimates, but achieves high accuracy ...
Swartz, J., Bremermann, Hans Joachim
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Parametric estimation with a class of M-estimators

Mathematical Methods of Statistics, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Estimating the Variance of a Kernel Density Estimation

2010
This article proposes an interval-valued extension of kernel density estimation. We show that the imprecision of this interval-valued estimation is highly correlated with the variance of the density estimation induced by the statistical variations of the set of observations.
Bilal Nehme, Olivier Strauss, Kevin Loquin   +2 more
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THE GEOMETRY OF ESTIMATION

Biometrika, 1951
Durbin, J., Kendall, M. G.
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On \(L\)-estimators viewed as \(M\)-estimators

Kybernetika, 1994
Summary: Arithmetical mean and median usually serve as basic examples of \(M\)- estimators. Both of them are \(L\)-estimators. Thus there is a natural question whether there are some other \(L\)-estimators which are \(M\)- estimators as well. We shall show that, with rare exceptions, this is not the case.
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