fix

R/get_loglikelihood.R

@@ -494,6 +494,9 @@ get_loglikelihood.phyloglm <- get_loglikelihood.phylolm
         # first derivative of 1/x is -1/x^2 - we cannot take the log from negative
         # values, so this won't work here, and we return NULL
         NULL
+      } else if (trans == "scale") {
+        scale_denominator <- .extract_scale_denominator(x)
+        .weighted_sum(log(1 / scale_denominator), w = model_weights)
       } else if (trans == "power") {
         trans_power <- .extract_power_transformation(x)
         .weighted_sum(log(trans_power * (get_response(x, as_proportion = TRUE)^(trans_power - 1))), w = model_weights) # nolint

R/get_transformation.R

@@ -107,7 +107,7 @@ get_transformation <- function(x, verbose = TRUE) {
 
 
 .extract_scale_denominator <- function(model) {
-  resp_term <- find_terms(x)[["response"]]
+  resp_term <- find_terms(model)[["response"]]
   # more complicated case: scale is inside `I()`
   if (startsWith(resp_term[1], "I(")) {
     as.numeric(gsub("(.*)/(.*)\\)", "\\2", resp_term[1]))

tests/testthat/test-get_transformation.R

@@ -13,3 +13,16 @@ test_that("get_transformation - detect powers", {
   expect_equal(fun$transformation(2), 25.99208, tolerance = 1e-3)
   expect_equal(fun$inverse(25.99208), 2, tolerance = 1e-3)
 })
+
+
+test_that("get_transformation - detect scale", {
+  data(mtcars)
+  m <- lm(mpg / 0.7 ~ hp, data = mtcars)
+  fun <- get_transformation(m)
+  expect_equal(fun$transformation(2), 2 / 7, tolerance = 1e-3)
+  expect_equal(fun$inverse(2.857143), 2, tolerance = 1e-3)
+  m <- lm(I(mpg / 0.7) ~ hp, data = mtcars)
+  fun <- get_transformation(m)
+  expect_equal(fun$transformation(2), 2 / 7, tolerance = 1e-3)
+  expect_equal(fun$inverse(2.857143), 2, tolerance = 1e-3)
+})