add test for tweedie

R/pkg/DESCRIPTION

@@ -21,7 +21,8 @@ Suggests:
     rmarkdown,
     testthat,
     e1071,
-    survival
+    survival,
+    statmod
 Collate:
     'schema.R'
     'generics.R'

R/pkg/R/mllib_regression.R

@@ -86,9 +86,9 @@ setClass("IsotonicRegressionModel", representation(jobj = "jobj"))
 #' summary(savedModel)
 #'
 #' # fit tweedie model
-#' library(statmod)
+#' require(statmod)
 #' model <- spark.glm(df, Sepal_Length ~ Sepal_Width, 
-#'   family = tweedie(var.power = 1.5, link.power = 0))
+#'   family = tweedie(var.power = 1.2, link.power = 0))
 #' summary(model)
 #' }
 #' @note spark.glm since 2.0.0

R/pkg/inst/tests/testthat/test_mllib_regression.R

@@ -77,6 +77,18 @@ test_that("spark.glm and predict", {
   out <- capture.output(print(summary(model)))
   expect_true(any(grepl("Dispersion parameter for gamma family", out)))
 
+  # tweedie family
+  require(statmod)
+  model <- spark.glm(training, Sepal_Width ~ Sepal_Length + Species,
+                     family = tweedie(var.power = 1.2, link.power = 1.0))
+  prediction <- predict(model, training)
+  expect_equal(typeof(take(select(prediction, "prediction"), 1)$prediction), "double")
+  vals <- collect(select(prediction, "prediction"))
+  rVals <- suppressWarnings(predict(
+    glm(Sepal.Width ~ Sepal.Length + Species, data = iris, 
+        family = tweedie(var.power = 1.2, link.power = 1.0)), iris))
+  expect_true(all(abs(rVals - vals) < 1e-6), rVals - vals) 
+
   # Test stats::predict is working
   x <- rnorm(15)
   y <- x + rnorm(15)