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It parses a model or uses an already parsed model to return a Tidy Eval formula that can then be used inside a dplyr command.

Usage

tidypredict_interval(model, interval = 0.95)

Arguments

model

An R model or a list with a parsed model

interval

The prediction interval, defaults to 0.95

Details

The result still has to be added to and subtracted from the fit to obtain the upper and lower bound respectively.

Examples


model <- lm(mpg ~ wt + cyl * disp, offset = am, data = mtcars)
tidypredict_interval(model)
#> 2.05183051648029 * sqrt((-0.176776695296637) * (-0.176776695296637) * 
#>     6.20704821338125 + (-0.590557271637747 + wt * 0.183559646169165) * 
#>     (-0.590557271637747 + wt * 0.183559646169165) * 6.20704821338125 + 
#>     (-0.257207134290773 + wt * -0.230680634727453 + cyl * 0.161513439412957) * 
#>         (-0.257207134290773 + wt * -0.230680634727453 + cyl * 
#>             0.161513439412957) * 6.20704821338125 + (-0.868335233010594 + 
#>     wt * 0.271667738147758 + cyl * 0.169308509351746 + disp * 
#>     -0.00456516834027639) * (-0.868335233010594 + wt * 0.271667738147758 + 
#>     cyl * 0.169308509351746 + disp * -0.00456516834027639) * 
#>     6.20704821338125 + (-1.53184887490412 + wt * -0.163034819828352 + 
#>     cyl * 0.221405540626369 + disp * 0.0170837100474746 + cyl * 
#>     disp * -0.0020081028047214) * (-1.53184887490412 + wt * -0.163034819828352 + 
#>     cyl * 0.221405540626369 + disp * 0.0170837100474746 + cyl * 
#>     disp * -0.0020081028047214) * 6.20704821338125 + 6.20704821338125)