Description Usage Arguments Value See Also

`new_fullrank_kinship`

, `new_fullrank_K`

, `new_fullrank_UD`

,
`new_lowrank_kinship`

, `new_lowrank_K`

and `new_lowrank_UD`

create the ggmix objects from the provided data that are necessary to fit the
penalized linear mixed model according to the user's parameters.

1 2 3 4 5 6 7 8 9 10 11 | ```
new_fullrank_kinship(x, y, kinship)
new_fullrank_K(x, y, K)
new_fullrank_UD(x, y, U, D)
new_lowrank_kinship(x, y, kinship, n_nonzero_eigenvalues, n_zero_eigenvalues)
new_lowrank_K(x, y, K, n_nonzero_eigenvalues, n_zero_eigenvalues)
new_lowrank_UD(x, y, U, D, n_nonzero_eigenvalues, n_zero_eigenvalues)
``` |

`x` |
input matrix, of dimension n x p; where n is the number of observations and p are the number of predictors. |

`y` |
response variable. must be a quantitative variable |

`kinship` |
positive definite kinship matrix |

`K` |
the matrix of SNPs used to determine the kinship matrix |

`U` |
left singular vectors corresponding to the non-zero eigenvalues
provided in the |

`D` |
non-zero eigenvalues. This option is provided to the user should
they decide or need to calculate the eigen decomposition of the kinship
matrix or the singular value decomposition of the matrix of SNPs used to
calculate the kinship outside of this function. This may occur, if for
example, it is easier (e.g. because of memory issues, it's easier to
calculate in plink). This should correspond to the non-zero eigenvalues
only. Note that if you are doing an |

`n_nonzero_eigenvalues` |
the number of nonzero eigenvalues. This argument
is only used when |

`n_zero_eigenvalues` |
the number of desired or specified zero eigenvalues.
This is only needed when |

A ggmix object, of the class that corresponds to the estimation method. These objects are lists that contain the data necessary for computation. These functions are not meant to be called directly by the user

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