Simulate and Diagnose (Generalized) Linear Models

Documentation for package ‘regressinator’ version 0.1.2

augment_longer	Augment a model fit with residuals, in "long" format
binned_residuals	Obtain binned residuals for a model
bin_by_interval	Group a data frame into bins
bin_by_quantile	Group a data frame into bins
by_level	Convert factor levels to numeric values
custom_family	Family representing a GLM with custom distribution and link function
decrypt	Decrypt message giving the location of the true plot in a lineup
empirical_link	Empirically estimate response values on the link scale
model_lineup	Produce a lineup for a fitted model
ols_with_error	Family representing a linear relationship with non-Gaussian errors
parametric_boot_distribution	Simulate the distribution of estimates by parametric bootstrap
partial_residuals	Augment a model fit with partial residuals for all terms
population	Define the population generalized regression relationship
predictor	Specify the distribution of a predictor variable
response	Specify a response variable in terms of predictors
rfactor	Draw random values from a factor variable
sample_x	Draw a data frame from the specified population.
sample_y	Draw a data frame from the specified population.
sampling_distribution	Simulate the sampling distribution of estimates from a population