Lazily prepare a model inference

prepare_model() attaches a model specification to a <def_var> object, producing a <model_lazy> ready for optional recalibration with via() before being executed with conclude().

Usage

prepare_model(.x, .model_fn, ...)

Arguments

.x

An S7 object extension yielded by, e.g. <def_var> object from define_model(), or an <expanded_model> object from write_models().

.model_fn

A model function such as LINEAR_REG().

...

Additional arguments passed to methods.

Value

A <model_lazy> S7 object.

See also

prepare_test(), define_model(), via(), conclude()

Examples

mtcars |>
    define_model(rel(mpg, wt)) |>
    prepare_model(LINEAR_REG) |>
    conclude()
#> 
#> == Model ======================================================================= 
#> 
#> Variable Mapper : rel 
#> Args : mpg ; wt 
#>     x_vars : 1 
#>     resp_vars : 1 
#> 
#> == Linear Regression =========================================================== 
#> 
#> -- Coefficients ----------------------------------------------------------------
#> 
#> ──────────────┬───────────────────────────────────────────
#>   term        │  estimate  std_error  statistic  p_value  
#> ──────────────┼───────────────────────────────────────────
#>   (Intercept) │   6.047      0.309     19.590    <0.001   
#>   mpg         │   -0.141     0.015     -9.559    <0.001   
#> ──────────────┴───────────────────────────────────────────
#> 
#> 
#> -- Model Fit -------------------------------------------------------------------
#> 
#> Warning: running command 'tput cols' had status 2
#> ------------------------------------------------------
#>   R Squared      :    0.75    F-statistic :    91.38
#>   Adj. R Squared :    0.74    df1         :        1
#>   Sigma          :    0.49    df2         :       30
#>   n              :      32    p-value     :   <0.001
#>   df (residual)  :      30                :         
#> ------------------------------------------------------
#> 
#>