R: Simulate and Diagnose (Generalized) Linear Models

# Simulate and Diagnose (Generalized) Linear Models

## Documentation for package ‘regressinator’ version 0.3.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

augment_longer | Augment a model fit with residuals, in "long" format
augment_quantile | Augment data with randomized quantile residuals
augment_quantile_longer | Augment data with randomized quantile residuals
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