# Diagnostic plots for the robust regression model with compositional covariats

### Description

Plot the response or the model diagnostic plots for robust linear regression model with compositional data

### Usage

1 2 3 4 5 6 7 | ```
## S3 method for class 'complmrob'
plot(x, y = NULL, type = c("response", "model"),
se = TRUE, conf.level = 0.95, scale = c("ilr", "percent"),
theme = ggplot2::theme_bw(), pointStyle = list(color = "black", size =
ggplot2::rel(1), alpha = 1, shape = 19), lineStyle = list(color = "grey20",
width = ggplot2::rel(1), linetype = "solid"), seBandStyle = list(color =
"gray80", alpha = 0.5), stack = c("horizontal", "vertical"), ...)
``` |

### Arguments

`x` |
the object returned by |

`y` |
ignored. |

`type` |
one of |

`se` |
should the confidence interval be shown in the response plot. |

`conf.level` |
if the confidence interval is shown in the response plot, this parameter sets the level of the confidence interval. |

`scale` |
should the x-axis in the response plot be in percentage or in the ILR-transformed scale? |

`theme` |
the ggplot2 theme to use for the response plot. |

`pointStyle` |
a list with style parameters for the points in the response plot (possible entries
are |

`lineStyle` |
list with style parameters for the smoothing lines in the response plot (possible entries
are |

`seBandStyle` |
a list with style parameters ( |

`stack` |
how the facets are laid out in the response plot. |

`...` |
futher arguments to the model diagnostic plot method (see |

### Details

The response plot shows the value on the first component of the orthonormal basis versus the response and the fitted values. For the fitted values, the other components are set to the median of the values in that direction, this may change in the future, as it is sub-optimal.

For the model diagnostic plots see the details in the help file for `plot.lmrob`

.
The model diagnostic plots are the same for all sub-models fit to the data transformed with the different
orthonormal basis.

### Examples

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