Description Usage Arguments Value Note

This function checks the KKT conditions

1 2 3 4 5 |

`eta` |
current estimate of the eta parameter |

`sigma2` |
current estimate of the sigma2 parameter |

`beta` |
current estimate of the beta parameter including the intercept. this should be of length p+1, where p is the number of variables. |

`eigenvalues` |
non-zero eigenvalues of the kinship matrix, or the square of the singular values of the matrix used to construct the kinship matrix |

`x` |
rotated x. Should be U^T X, where U is the matrix of eigenvectors
and X contains the first column of ones for the intercept. x should be a
mtrix of dimension n x (p+1). These are outputted by the constructor
functions. See |

`y` |
rotated y. Should be U^T Y, where U is the matrix of eigenvectors and Y is the response. |

`nt` |
total number of observations |

`lambda` |
A user supplied lambda sequence (this is the tuning parameter). Typical usage is to have the program compute its own lambda sequence based on nlambda and lambda.min.ratio. Supplying a value of lambda overrides this. WARNING: use with care. Do not supply a single value for lambda (for predictions after CV use predict() instead). Supply instead a decreasing sequence of lambda values. glmnet relies on its warms starts for speed, and its often faster to fit a whole path than compute a single fit. |

`tol.kkt` |
Tolerance for determining if an entry of the subgradient is zero |

returns the values of the gradient for each of the parameters

`grr_sigma2`

and `grr_beta0`

are functions for the gradient
of sigma2 and beta0, respectively

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.