Description Usage Arguments Value

Fisher score method for estimating the regression coeffcients in a mixture of logisitc regression.

1 |

`Y` |
The response variable. Must be binary. |

`X` |
The design matrix. Intercept included. |

`alpha` |
The initial values of the coefficients for the confounders. |

`beta` |
The initial value of the coefficient for the true somatic mutation value. |

`T0S` |
The weights vector for the mixture when the true somatic muation equals 0. |

`T1S` |
The weights vector for the mixture when the true somatic muation equals 1. |

`converged` |
The tolerance for the convergence. Default is 1e-6. |

`maxIT` |
The maximal number of the EM iteration times. Default is 200. |

The estimated regression coefficients.

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