Description Usage Arguments Details Value References See Also Examples

`gen_bin_data`

generate the data used for the model experiment

1 | ```
gen_bin_data(beta, N, nclass, seed)
``` |

`beta` |
A numeric vector that represents the true coefficients that used to generate the synthesized data. |

`N` |
A numeric number specifying the number of the synthesized data. It should be an integer. |

`nclass` |
A numeric number used to specify how many clusters the original data would be transformed into. It should be an integer. |

`seed` |
Set random number seed. |

The function gen_bin_data generates N points. That is,the first column of the design matrix is 1 and the second column has a normal distribution with a mean of 1 and a variance of 1 and the rest columns with a mean of 0 and a variance of 1. Next, they are clustered into classes to decrease the computation cost. You should specify the number of classes. In the function, it's the parameter nclass.

a list of seven elements:

`data.clust` |
list with clustering results. Samples in the same list element are closer with each other |

`X` |
the samples with the smallest variance from each cluster. Note that the length of X is the same as the number of data.clust |

`y` |
the target value of 0 or 1 corresponding to X |

Wang Z, Kwon Y, Chang YcI (2019). Active learning for binary classification with variable selection. arXiv preprint arXiv:1901.10079.

`gen_multi_data`

for categorical and ordinal case

`gen_GEE_data`

for generalized estimating equations case.

1 | ```
# For an example, see example(seq_bin_model)
``` |

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