Parse the covariates and model components from given data and formula

create_model.covs_and_comps(data, model_formula, x_cont_scl, verbose)

## Arguments

data A data.frame where each column corresponds to one variable, and each row is one observation. Continuous covariates and the response variable must have type "numeric" and categorical covariates must have type "factor". Missing values should be indicated with NaN or NA. The response variable cannot contain missing values. Column names should not contain trailing or leading underscores. an object of class lgpformula Information on how to scale the continuous covariates. This can either be an existing list of objects with class lgpscaling, or NA, in which case such list is created by computing mean and standard deviation from data Should some informative messages be printed?

## Value

parsed input to Stan and covariate scaling, and other info

Other internal model creation functions: create_model.formula(), create_model.likelihood(), create_model.prior()