Description Usage Arguments Value

REML EM algorithm for estimating variance components

1 2 3 4 5 6 7 8 9 10 11 | ```
estimate.vc(
y,
Xtilde,
qrXtilde,
beta,
G,
init.sigma = 0.5,
init.tau = 0.5,
tol = 0.001,
maxiters = 1000
)
``` |

`y` |
Vector of observed phenotypes |

`Xtilde` |
Matrix of covariates (first column contains the intercept, last column contains the E factor for studying the GxE effect) |

`qrXtilde` |
Object containing QR decomposition of Xtilde |

`beta` |
Coefficient vector for covariate matrix Xtilde |

`G` |
Matrix of genotype markers |

`init.sigma` |
Initial sigma input (Default is 0.5) |

`init.tau` |
Initial tau input (Default is 0.5) |

`tol` |
Tolerance for convergence (Default is 1e-3) |

`maxiters` |
Maximum number of iterations (Default is 1000) |

Estimates for tau and sigma

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