Description Usage Arguments Value Author(s) References Examples

Calculating the prior probability of linear and nonlinear classes of BNN models.

1 | ```
BNNprior(dimX, dimY, hid_num = 3,lambda=0.025,total_iteration=1000000,popN = 20)
``` |

` dimX ` |
Dimension of the input data. |

` dimY ` |
The dimension of reponse data. It is restricted to 1 in the current version of the package. |

` hid_num ` |
Number of hidden units. The default setting is 3. |

`lambda` |
The prior probability for each connection of the neural network being selected for the final model. The default setting is 0.025. |

` total_iteration ` |
Number of total iterations, default of 1000,000. |

` popN ` |
Number of Markov Chains, default of 20. |

`prob` |
Prior probability assigned to the class of linear models. |

Bochao Jia and Faming Liang

Liang, F., Li, Q., and Zhou, L. (2017). Bayesian Neural Networks for Selection of Drug Sensitive Genes. Journal of the American Statistical Association.

1 2 |

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