test_that("rout_fitter", {

  x = c(0, 2^(-4:4))
  theta = c(0, 100, log(.5), 2)
  y = c(99.91, 96.892, 90.782, 79.24, 51.838, 18.849, 7.098, -1.697, 0.278, 1.136)

  fit1 = rout_fitter(NULL, hill_model, x=x, y=y)
  fit2 = rout_fitter(c( theta, log(2) ), hill_model, x=x, y=y)
  
  expect_true(sum(fit1$outlier.adj)==0)
  expect_true(sum(fit2$outlier.adj)==0)
  
  ii = c(6, 9)
  y[ii] = hill_model(theta, x[ii]) + 15

  fit3 = rout_fitter(c( theta, log(2) ), hill_model, x=x, y=y, Q=0.05)
  expect_true(sum(fit3$outlier)==2)
  expect_true(sum(fit3$outlier.adj)==0)

  fit3 = rout_fitter(c( theta, log(2) ), hill_model, x=x, y=y, Q=0.1)
  expect_true(sum(fit3$outlier)==2)
  expect_true(sum(fit3$outlier.adj)==2)  

  ## hill_quad_model
  theta = c(0, 100, 2, 1, -0.5)          ## Model parameters
  y = c(-3.204, -3.269, 4.488, 41.994, 69.658, 85.627, 90.797, 101.094, 83.925, 72.863)
  fit1 = rout_fitter(NULL, hill_quad_model, x=x, y=y, Q=0.01 )
  expect_true(sum(fit1$outlier.adj)==0)  

  ii = c(3, 7)
  y[ii] = hill_quad_model(theta, x[ii]) - 30
  fit2 = rout_fitter(NULL, hill_quad_model, x=x, y=y, Q=0.1 )
  expect_true(sum(fit2$outlier)==2)
  expect_true(sum(fit2$outlier.adj)==2) 

  
})