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 ...
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 ...
An important problem in multivariate statistics is the estimation of covariance matrices. We consider a class of nonparametric covariance models in which the entries in the covariance matrix depend on ...
Graphical models provide a robust framework for representing the conditional independence structure between variables through networks, enabling nuanced insight into complex high-dimensional data.
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