Create, Visualize, and Predict with Models

AARP | Prices for life insurance |

Alder | Nitrogen fixing by alder plants |

Birth_weight | Birth weights and maternal data |

College_grades | Grades at a small college |

collinearity | Calculate measures of collinearity |

construct_fitting_call | Construct a call for refitting a model from the model itself |

Crime | Data from the US FBI Uniform Crime Report, 1960 |

data_from_mod | Extract training data from model |

df_counts | Formula interface to counts |

df_props | Joint and conditional proportions |

df_typical | Find typical levels of explanatory variables in a... |

explanatory_vars | Get the names of the explanatory or response variables in a... |

formula_from_mod | Extract the model formula used in specifying the model |

HDD_Minneapolis | Heating degree days in Minneapolis, Minnesota, USA |

Houses_for_sale | Houses for sale |

mod_cv | Compare models with k-fold cross validation |

mod_effect | Calculate effect sizes in a model |

mod_ensemble | Create bootstrapped ensembles of a model |

mod_error | Mean square prediction error |

mod_eval | Evaluate a model for specified inputs |

mod_eval_fun | Internal functions for evaluating models |

mod_eval_grid | Create discrete levels of explanatory variables in a... |

mod_fun | Transforms a model into a function of inputs -> output |

mod_plot | Plot out model values |

mosaicModel | 'mosaicModel' package |

Mussels | Metabolism of zebra mussels |

NCI60_snippet | Gene expression in cancer cells. |

Oil_history | Historical production of crude oil, worldwide 1880-2014 |

reference_values | Compute sensible values from a data set for use as a baseline |

Runners | Performance of runners in a ten-mile race as they age |

School_data | Simulated data bearing on school vouchers |

Tadpoles | Swimming speed of tadpoles. |

Trucking_jobs | Earnings of workers at a trucking company. |

Used_Fords | Prices of used Ford automobiles in 2009 |

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