Journal of the Royal Statistical Society. Series D (The Statistician), Vol. 48, No. 4 (1999), pp. 477-493 (17 pages) Many papers have addressed the problem of fitting a straight line to a set of ...

This is a preview. Log in through your library . Abstract Genetic potential for evolutionary change and covariational constraints are typically summarized as the genetic variance-covariance matrix G, ...

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 ...

The COV= option must be specified to compute an approximate covariance matrix for the parameter estimates under asymptotic theory for least-squares, maximum-likelihood, or Bayesian estimation, with or ...

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 ...

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 ...

Where is the model fitting information stored in MLwiN? Parameter storage columns: MLwiN routinely stores the random parameter estimates in C1096 (for more information see the question ' Where can I ...

Mary Hall is a editor for Investopedia's Advisor Insights, in addition to being the editor of several books and doctoral papers. Mary received her bachelor's in English from Kent State University with ...

Data clustering is the process of grouping data items so that similar items are placed in the same cluster. There are several different clustering techniques, and each technique has many variations.