Description Usage Arguments Value Examples

View source: R/givitiCalibrationBasic.R

`polynomialLogRegrFw`

implements a forward selection in a
polynomial logistic regression model.

1 | ```
polynomialLogRegrFw(data, thres, maxDeg, startDeg)
``` |

`data` |
A |

`thres` |
A numeric scalar between 0 and 1 representing the significance level adopted in the forward selection. |

`maxDeg` |
The maximum degree considered in the forward selection. |

`startDeg` |
The starting degree in the forward selection. |

A list containing the following components:

- fit
An object of class

`glm`

containig the output of the fit of the logistic regression model at the end of the iterative forward selection.- m
The degree of the polynomial at the end of the forward selection.

1 2 3 4 5 | ```
e <- runif(100)
logite <- logit(e)
o <- rbinom(100, size = 1, prob = e)
data <- data.frame(e = e, o = o, logite = logite)
polynomialLogRegrFw(data, .95, 4, 1)
``` |

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