tests/testthat/test-sens-fd.R

In nlmixr: Nonlinear Mixed Effects Models in Population PK/PD

nlmixrTest(
  {
    f <- function() {
      ini({
        popKe <- 0.5
        etaKe ~ 0.04
        etaF ~ 0.1
        fp <- 2
        prop.sd <- 0.1
      })
      model({
        ke <- popKe * exp(etaKe)
        d / dt(ipre) <- -ke * ipre
        f(ipre) <- fp * exp(etaF)
        ipre ~ prop(prop.sd)
      })
    }

    set.seed(42)
    dat <- Wang2007
    dat$DV <- dat$Y
    dat2 <- dat[dat$Time == 0, ]
    dat2$EVID <- 101
    dat2$AMT <- 10
    dat2 <- rbind(dat2, data.frame(dat, EVID = 0, AMT = 0))
    dat2 <- dat2[(order(dat2$ID, -dat2$EVID, dat2$Time)), ]
    dat2 <- dat2[, names(dat2) != "Y"]
    dat3 <- data.frame(ID = 1:10, f0 = 2 * exp(rnorm(10, sd = 0.1)))
    dat2 <- merge(dat2, dat3)
    dat2$DV <- dat2$DV * dat2$f0

    testIt <- function(meth) {
      context(sprintf("test finite difference sensitivities in %s", meth))
      test_that(sprintf("finite difference %s", meth), {
        suppressWarnings({
          fit <- nlmixr(f, dat2, "focei",
            control = foceiControl(maxOuterIterations = 0, covMethod = "")
          )
          expect_false(all(fit$eta$etaF == 0))

          fit <- nlmixr(f, dat2, "focei",
            control = foceiControl(maxOuterIterations = 0, covMethod = "", eventCentral = FALSE)
          )
          expect_false(all(fit$eta$etaF == 0))
        })
      })
    }

    lapply(c("focei", "foce", "foi", "fo"), testIt)
  },
  test = "focei"
)