Modelling Functions that Work with the Pipe

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Documentation for package ‘modelr’ version 0.1.6

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add_predictions Add predictions to a data frame
add_predictors Add predictors to a formula
add_residuals Add residuals to a data frame
bootstrap Generate 'n' bootstrap replicates.
crossv_kfold Generate test-training pairs for cross-validation
crossv_loo Generate test-training pairs for cross-validation
crossv_mc Generate test-training pairs for cross-validation
data_grid Generate a data grid.
fit_with Fit a list of formulas
formulae Create a list of formulas
formulas Create a list of formulas
gather_predictions Add predictions to a data frame
gather_residuals Add residuals to a data frame
geom_ref_line Add a reference line (ggplot2).
heights Height and income data.
mae Compute model quality for a given dataset
mape Compute model quality for a given dataset
model-quality Compute model quality for a given dataset
model_matrix Construct a design matrix
mse Compute model quality for a given dataset
na.warn Handle missing values with a warning
permute Generate 'n' permutation replicates.
permute_ Generate 'n' permutation replicates.
qae Compute model quality for a given dataset
resample A "lazy" resample.
resample_bootstrap Generate a boostrap replicate
resample_partition Generate an exclusive partitioning of a data frame
resample_permutation Create a resampled permutation of a data frame
rmse Compute model quality for a given dataset
rsae Compute model quality for a given dataset
rsquare Compute model quality for a given dataset
seq_range Generate a sequence over the range of a vector
sim Simple simulated datasets
sim1 Simple simulated datasets
sim2 Simple simulated datasets
sim3 Simple simulated datasets
sim4 Simple simulated datasets
spread_predictions Add predictions to a data frame
spread_residuals Add residuals to a data frame
typical Find the typical value