us_deaths$off <- log(us_deaths$population) f <- deaths ~ gender + age_group + year f_off <- update(f, ~ . + off) y <- us_deaths$deaths x <- model.matrix(f, us_deaths)[, -1] x_off <- model.matrix(update(f, ~. + off), us_deaths)[, -1] # base models glm_base <- glm(f, family = "poisson", us_deaths, offset = off) glmnet_base <- glmnet::glmnet(x, y, family = "poisson", offset = us_deaths$off, alpha = 0.25) rec <- recipes::recipe(deaths ~ gender + age_group + year + off, data = us_deaths) |> recipes::step_rename(offset = off) test_that("*_offset() models work", { # glm_offset glm_off <- glm_offset(f, family = "poisson", us_deaths, offset_col = "off") expect_identical(predict(glm_base), predict(glm_off)) # glmnet_offset glmnet_off <- glmnet_offset(x_off, y, family = "poisson", offset_col = "off", alpha = 0.25) expect_identical(predict(glmnet_base, x, newoffset = us_deaths$off, s = 1E-5), predict(glmnet_off, x, newoffset = us_deaths$off, s = 1E-5)) }) test_that("poisson_reg_offset() works", { # glm offset glm_off <- poisson_reg_offset() |> set_engine("glm_offset", offset_col = "off") |> fit(f, data = us_deaths) expect_identical(predict(glm_base, type = 'response') |> unname(), predict(glm_off, us_deaths)$.pred) expect_identical(predict(glm_base), predict(glm_off, us_deaths, type = "raw")) # glmnet offset glmnet_off <- poisson_reg_offset(penalty = 1E-5, mixture = 0.25) |> set_engine("glmnet_offset", offset_col = "off") |> fit(f_off, data = us_deaths) expect_identical(predict(glmnet_base, x, newoffset = us_deaths$off, s = 1E-5, type = 'response') |> as.numeric(), predict(glmnet_off, us_deaths)$.pred) expect_identical(predict(glmnet_base, x, newoffset = us_deaths$off, s = 1E-5), predict(glmnet_off, us_deaths, type = "raw")) }) test_that("poisson_reg_offset() works with recipes", { # glm offset glm_off <- workflows::workflow() |> workflows::add_recipe(rec) |> workflows::add_model(poisson_reg_offset() |> set_engine("glm_offset")) |> fit(data = us_deaths) expect_identical(predict(glm_base, type = 'response') |> unname(), predict(glm_off, us_deaths)$.pred) # glmnet offset rec <- rec |> recipes::step_dummy(recipes::all_nominal_predictors()) glmnet_off <- workflows::workflow() |> workflows::add_recipe(rec) |> workflows::add_model(poisson_reg_offset(penalty = 1E-5, mixture = 0.25) |> set_engine("glmnet_offset")) |> fit(data = us_deaths) # re-do the baseline glmnet fix - columns are in a different order after the # recipe x <- rec |> recipes::prep() |> recipes::juice() |> as.matrix() x <- x[, !colnames(x) %in% c("offset", "deaths")] glmnet_base <- glmnet::glmnet(x, y, family = "poisson", offset = us_deaths$off, alpha = 0.25) expect_identical(predict(glmnet_base, x, newoffset = us_deaths$off, s = 1E-5, type = 'response') |> as.numeric(), predict(glmnet_off, us_deaths)$.pred) }) test_that("finalize works", { mod_spec <- poisson_reg_offset(penalty = tune(), mixture = tune()) |> set_engine("glmnet_offset") rec <- rec |> recipes::step_dummy(recipes::all_nominal_predictors()) wf <- workflows::workflow() |> workflows::add_model(mod_spec) |> workflows::add_recipe(rec) param_grid <- data.frame(penalty = 0.005, mixture = 0.9) expect_no_error(tune::finalize_workflow(wf, param_grid) |> fit(us_deaths)) expect_equal(tune::finalize_model(mod_spec, param_grid)$args |> lapply(rlang::eval_tidy), list(penalty = 0.005, mixture =0.9)) })