Man pages for regressinator
Simulate and Diagnose (Generalized) Linear Models

augment_longerAugment a model fit with residuals, in "long" format
augment_quantileAugment data with randomized quantile residuals
bin_by_intervalGroup a data frame into bins
binned_residualsObtain binned residuals for a model
by_levelConvert factor levels to numeric values
check_data_argCheck that the model fit uses the data argument to provide...
custom_familyFamily representing a GLM with custom distribution and link...
decryptDecrypt message giving the location of the true plot in a...
detect_transmutationDetect transmutation in formulas, such as factor(), and raise...
drop_factorsDrop factor columns from a data frame
empirical_linkEmpirically estimate response values on the link scale
factor_columnsCheck whether each column in a data frame is a factor
in_interactionDetermine if a predictor is involved in an interaction
model_lineupProduce a lineup for a fitted model
normalize_familyAccept family arguments in the same way as glm(), convert to...
ols_with_errorFamily representing a linear relationship with non-Gaussian...
parametric_boot_distributionSimulate the distribution of estimates by parametric...
partial_residualsAugment a model fit with partial residuals for all terms
populationDefine the population generalized regression relationship
population_predictorsGet the predictors of a population
population_responseGet the response variables of a population
predictorSpecify the distribution of a predictor variable
prototype_forGet a prototype data frame for partial residuals
regressinator-packageregressinator: Simulate and Diagnose (Generalized) Linear...
responseSpecify a response variable in terms of predictors
rfactorDraw random values from a factor variable
sample_xDraw a data frame from the specified population.
sampling_distributionSimulate the sampling distribution of estimates from a...
regressinator documentation built on Sept. 11, 2024, 6:50 p.m.