This is a preview. Log in through your library . Abstract This paper adds motivations for the use of the sample variance-covariance matrix estimator $\hat{\Sigma}$ in repeated measurement designs by: ...
The BLOCKS statement finds a design that maximizes the determinant |X'AX| of the treatment information matrix, where A depends on the block or covariate model. Alternatively, you can directly specify ...
The Annals of Mathematical Statistics, Vol. 27, No. 3 (Sep., 1956), pp. 737-748 (12 pages) The sampling variance of the least squares estimates of the components of variance in an unbalanced ...
This section provides an overview of a likelihood-based approach to general linear mixed models. This approach simplifies and unifies many common statistical analyses, including those involving ...
This paper proposes a novel shrinkage estimator for high-dimensional covariance matrices by extending the Oracle Approximating Shrinkage (OAS) of Chen et al. (2009) to target the diagonal elements of ...
The distribution of genetic variation among multiple traits is a key determinant of how a population will respond to selection (Lande, 1979; Schluter, 1996; Arnold et al., 2001). For the prediction of ...
You can use covariance and contravariance to provide polymorphic extension to delegates, arrays, and generics in C#. Here’s how. The C# programming language provides support for variance in two ways: ...
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