Plots the the Moran's I test of the response and the predictors in a training data frame.

plot_training_df_moran(
data = NULL,
dependent.variable.name = NULL,
predictor.variable.names = NULL,
distance.matrix = NULL,
distance.thresholds = NULL,
fill.color = viridis::viridis(100, option = "F", direction = -1),
point.color = "gray30"
)

## Arguments

data |
Data frame with a response variable and a set of predictors. Default: `NULL` |

dependent.variable.name |
Character string with the name of the response variable. Must be in the column names of `data` . If the dependent variable is binary with values 1 and 0, the argument `case.weights` of `ranger` is populated by the function `case_weights()` . Default: `NULL` |

predictor.variable.names |
Character vector with the names of the predictive variables. Every element of this vector must be in the column names of `data` . Optionally, the result of `auto_cor()` or `auto_vif()` Default: `NULL` |

distance.matrix |
Squared matrix with the distances among the records in `data` . The number of rows of `distance.matrix` and `data` must be the same. If not provided, the computation of the Moran's I of the residuals is omitted. Default: `NULL` |

distance.thresholds |
Numeric vector, distances below each value are set to 0 on separated copies of the distance matrix for the computation of Moran's I at different neighborhood distances. If `NULL` , it defaults to `seq(0, max(distance.matrix)/4, length.out = 2)` . Default: `NULL` |

fill.color |
Character vector with hexadecimal codes (e.g. "#440154FF" "#21908CFF" "#FDE725FF"), or function generating a palette (e.g. `viridis::viridis(100)` ). Default: `viridis::viridis(100, option = "F", direction = -1)` |

point.color |
Character vector with a color name (e.g. "red4"). Default: `gray30` |

## Value

A ggplot2 object.

## Examples