Description Usage Arguments Details Value Examples

View source: R/igate.regressions.R

This function takes a data frame, a target variable and a list of ssv and produces a regression plot of each ssv against the target. The output can written as .png file into the current working directory. Also, summary statistics are provided.

1 2 3 |

`df` |
Data frame to be analysed. |

`target` |
Target varaible to be analysed. |

`ssv` |
A vector of suspected sources of variation. These are the variables
in |

`outlier_removal_target` |
Logical. Should outliers (with respect to the target variable)
be removed from df (default: |

`outlier_removal_ssv` |
Logical. Should outlier removal be performed for each ssv (default: |

`savePlots` |
Logical. If |

`image_directory` |
Directory to which plots should be saved. This is only used if |

Regression plots for each `ssv`

against `target`

are produced and
svaed to current working directory. Also a data frame with summary statistics is produced,
see **Value** for details.

The regression plots of `target`

against each `ssv`

are written as
.png file into the current working directory. Also, a data frame with the following
columns is output

`Causes` | The `ssv` that were analysed. |

`outliers_removed` | How many outliers (with respect to this `ssv` )
have been removed before fitting the linear model? |

`observations_retained` | After outlier removal was performed, how many observations were left and used to fit the model? |

`regression_plot` | Logical. Was fitting the model successful? It can fail, for example, if a ssv is constant. |

`r_squared` | r^2 value of model. |

`gradient, intercept` | Gradient and intercept of fitted model. |

1 | ```
igate.regressions(iris, target = "Sepal.Length")
``` |

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