Description Usage Arguments Details Value Author(s) Examples

A bivariated regression plane for external standard calibration is
calculated to later convert signals into concentration values.
It differs from `calibCurve`

in the number of explanatory
variables, 2 in this case. This function is useful when some
interference effect is being considered such as the magnification of
the interest species signal due to the presence of another (known) species
in the same sample.

1 2 3 |

`plane` |
Data frame of numeric vectors named 'Conc', 'Conc.S' and 'Signal'. The vectors must contain the concentrations of the main species (the one whose concentration in the samples is to be known) and the secondary species (the interferent), and the standard's signals, respectively. |

`badpoint` |
Numeric vector with the points to be ignored in the regresion. This allows the easy elimination of outliers without losing the stored measurement information. |

`plot` |
Logical. If |

`lines` |
Number of lines to use in the mesh of the plane in the plot. |

`theta` |
Azimuthal angle at which the plane is visualized. |

`phi` |
Altitude angle at which the plane is visualized. |

`xlab` |
Label for X axis (main species concentration). |

`ylab` |
Label for Y axis (secondary species concentration). |

`zlab` |
Label for Z axis (response). |

`pch` |
Plotting symbols available in R. |

`cex` |
The size of pch symbols. |

A linear method (i.e `lm()`

) is applied to obtain the
regression equation. The user must verify model assumptions
such as normal distribution of residuals.

Model of the calibration plane

Cristhian Paredes, craparedesca@unal.edu.co

Eduardo Rodriguez de San Miguel, erdsmg@unam.mx

1 2 3 | ```
data(planelithium)
planeModel <- calibPlane(plane = planelithium)
summary(planeModel$model)
``` |

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