Description Usage Arguments Details Value Author(s) References See Also

Get the vector of the scale hyperparameter.

1 2 | ```
get.scale.bayesH(nu0, R2 = 0.5, X, y, type = "bayesH")
``` |

`nu0` |
the vector with shape parameter(s) of (hyper) prior distribution for variance of each the regression coefficient(s) and error variance. |

`R2` |
the expected proportion of the variance of the response variable that can be explained by the model (r squared). |

`y` |
the vector of response variable of the model. |

`X` |
the incidence matrix. |

`type` |
it is a string which if were defined as “ridge” the function performs Bayesian ridge regression, otherwise, Bayes H model. |

The user must be provided the vector `nu0`

and all elements this vector
must be greater than zero. The strategy adopted here is based on Perez et. al.
(2010).

An object of class `vector`

with values of the scale parameters.

Renato Rodrigues Silva, [email protected]

Perez. et. al. (2010). Genomic-Enabled Prediction Based on Molecular Markers and Pedigree Using the Bayesian Linear Regression Package in R. Plant Genome. 2010; 3(2): 106-116. doi: 10.3835/plantgenome2010.04.0005.

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