Description Usage Arguments Details Value Author(s) Examples

The function estimates a logistic regression model with the Maximum-Likelihood Method.

1 | ```
logit(fml, dat)
``` |

`fml` |
Formula-object of the desired independent and dependent variables: formula.object <- as.formula("y ~ x1 + x2 + ... xn"). |

`dat` |
Data frame which contains the variables specified in the formula-object. |

Estimates a logistic regression for a binary independent variable where the data generating process can be described with a Bernoulli-distribution. Parameters are maximised with the Maximum-Likelihood-Method using a Quasi-Newton-Algorithm.

Output are the coefficient estimates of a logistic regression and its respective standard errors.

Johannes Besch, [email protected], Marco Radojevic [email protected]

1 2 3 |

RadojevicM/OLSLog2 documentation built on Nov. 18, 2017, 8:53 a.m.

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