• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 2
  • Tagged with
  • 3
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 2
  • 1
  • 1
  • 1
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Contributions à l'estimation pour petits domaines

Stefan, Marius 26 August 2005 (has links)
Dans la thèse nous nous occupons de l'estimation de la moyenne d'un petit domaine sous un modèle one-fold et utilisant MINQUE pour estimer les composantes de la variance, sous un modèle two-fold avec variances aléatoires, sous des plans noninformatifs et informatifs.
2

Maximum Likelihood Estimators of the Variance Components Based on the Q-Reduced Model

Lee, K. R., Kapadia, C. H. 01 January 1988 (has links)
In a variance component model,(Formula presented.), Pukelsheim (1981) proved that the non-negative and unbiased estimation of the variance components σ(Formula presented.), j=1, …, c, entails a transformation of the original model to Q(Formula presented.) (called Q-reduced model). The maximum likelihood (ML) approach based on the likelihood of Q(Formula presented.) (denoted Q-ML) is considered and applied to an incomplete block design (IBD) model. The Q-ML estimators of variance components and are shown to be more efficient in the mean squared error sense than the non-negative MINQUE’s (minimum norm quadratic unbiased estimators) in the IBD. The effect of using Q-ML estimators of the variance components to estimate the variance ratio in the combined estimator of the treatment contrast is also considered.
3

Contributions à l'estimation pour petits domaines

Stefan, Marius 26 August 2005 (has links)
Dans la thèse nous nous occupons de l'estimation de la moyenne d'un petit domaine sous un modèle one-fold et utilisant MINQUE pour estimer les composantes de la variance, sous un modèle two-fold avec variances aléatoires, sous des plans noninformatifs et informatifs. / Doctorat en sciences, Orientation statistique / info:eu-repo/semantics/nonPublished

Page generated in 0.0223 seconds