inst/doc/GetStarted.R

In additive: Bindings for Additive TidyModels

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library(additive)

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library(recipes)
library(workflows)

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set.seed(2020)
dat <- gamSim(1, n = 400, dist = "normal", scale = 2)

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test_recipe <- dat |>
  recipe() |>
  update_role(y, new_role = "outcome") |>
  update_role(x0, x1, x2, x3, new_role = "predictor") |>
  step_normalize(all_numeric_predictors())

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print(test_recipe)

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test_model <- additive(
    family = gaussian(),
    method = "REML"
  ) |>
  set_engine("mgcv") |>
  set_mode("regression")

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print(test_model)

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test_model <- test_model |>
  update(family = gaussian())

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test_workflow <- workflow() |>
  add_recipe(test_recipe) |>
  add_model(
    spec = test_model,
    formula = y ~ s(x0) + s(x1) + s(x2) + s(x3)
  )

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print(test_workflow)

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run_on_linux <- grepl("linux", R.Version()$os, ignore.case = TRUE)

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test_workflow_fit <- test_workflow |>
  fit(data = dat)

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print(test_workflow_fit)

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test_fit <- test_workflow_fit |>
  extract_fit_parsnip()

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gam_fit <- test_workflow_fit |>
  extract_fit_engine()

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class(gam_fit)

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newdata <- dat[1:5, ]

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test_workflow_fit |>
  predict(
    new_data = newdata,
    type = "conf_int",
    level = 0.95
  )

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test_workflow_fit |>
  predict(
    new_data = newdata,
    type = "conf_int",
    level = 0.95,
    std_error = TRUE
  )