nmTest({

  test_that("add+prop saem; issue nlmixr#503", {

    PKdata <- warfarin[warfarin$dvid == "cp", ]

    One.comp.KA.solved <- function() {
      ini({
        # Where initial conditions/variables are specified
        lka  <- log(1.15)  #log ka (1/h)
        lcl  <- log(0.135) #log Cl (L/h)
        lv   <- log(8)     #log V (L)
        prop.err <- 0.15   #proportional error (SD/mean)
        add.err  <- 0.6    #additive error (mg/L)
        eta.ka ~ 0.5   #IIV ka
        eta.cl ~ 0.1   #IIV cl
        eta.v  ~ 0.1   #IIV v
      })
      model({
        # Where the model is specified
        cl <- exp(lcl + eta.cl)
        v  <- exp(lv + eta.v)
        ka <- exp(lka + eta.ka)
        ## solved system example
        ## where residual error is assumed to follow proportional and additive error
        linCmt() ~ propT(prop.err) + add(add.err)
      })
    }

    fitOne.comp.KA.solved_S2 <-
      suppressMessages(nlmixr(
        One.comp.KA.solved,    #the model definition
        PKdata,                #the data set
        est = "saem",          #the estimation algorithm (SAEM)
        control=saemControl(nBurn = 200, #200 SAEM burn-in iterations (the default)
                            nEm   = 300, #300 EM iterations (the default)
                            print = 50,
                            #type="newuoa",
                            addProp="combined1"),
        table=tableControl(npde=TRUE, cwres=TRUE)
      ))

    expect_true(fitOne.comp.KA.solved_S2$theta["add.err"] > 0.4)
  })

})