Plot the fitted data set and linear decision boundary.

1 2 |

`x` |
object of class |

`fitdb` |
logical. If |

`initdb` |
logical. If |

`xlim` |
the x limits of the plot |

`ylim` |
the y limits of the plot |

`bg` |
the background color to be used for points. Default is |

`pch` |
the symbols to be used as points. Default is |

`...` |
further arguments. |

This function produces a scatter plot of data matrix in the `x`

and (optionally) decision boundary specified within (i.e., `x$par`

and/or `x$initpar`

).

The look of the plot differs depending on the dimension of the model. If the dimension is 1, the model matrix is plotted on the y-axis, and category vector (as in `x$category`

) is plotted on the x axis. If the dimension is 2, scatter plot of the model matrix is plotted. If the dimension is 3, `plot3d.glc`

is called to create a 3D scatter plot. If the dimension is greater than 3, an error message will be returned.

`plot3d.glc`

1 2 3 4 5 6 7 8 9 10 | ```
data(subjdemo_2d)
fit.2dl <- glc(response ~ x + y, data=subjdemo_2d,
category=subjdemo_2d$category, zlimit=7)
plot(fit.2dl)
#if one wants to plot decision bounds in
# colors different from the defaults
plot(fit.2dl, fitdb=FALSE)
abline(coef=coef(fit.2dl$par), col="orange")
abline(coef=coef(fit.2dl$initpar), col="purple")
``` |

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