Description Usage Arguments Details Value

Get the matrices W and H using the Rcpp package for the categorical case

1 |

`data` |
A matrix containing the training samples which we will use in the categorical case. |

`beta` |
A matrix contains the estimated coefficient. Note that the beta_mat is a n * k matrix which n is the number of the explanatory variables and k+1 is the number of categories |

getWH uses the current training data and the estimated coefficient under the categorical case to obtain the matrices W and H to further get the variance-covariance matrix and minimum eigenvalue. The variance-covariance matrix and minimum eigenvalue will be used in the process of selecting the new sampling and determining whether to stop the iteration. Note that using the Rcpp package can significantly reduce the time of operation and get conclusions faster.

a list contains several components including the variance-covariance matrix, minimum eigenvalue, W and H.

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