inst/models/values-1.1.1.3-U014_solve_saem-unix.R

In nlmixrdevelopment/nlmixr.examples: Nonlinear Mixed Effects Models in Population Pharmacokinetics and Pharmacodynamics

expected_values[[runno]] <- list(lik = c(-Inf, Inf, Inf), param = c(1.6041, 4.4703, NaN), 
    stdev_param = c(0.31903, 0.33745, NA), sigma = c(prop.err = NaN), 
    parFixedDf = structure(list(Estimate = c(lCl = 1.60409883727657, 
    lVc = 4.47032136291814, prop.err = NaN), SE = c(lCl = 0.0331888400128351, 
    lVc = 0.043230765764938, prop.err = NA), "%RSE" = c(2.06900218624825, 
    0.96706169993823, NA), "Back-transformed" = c(4.97337576186181, 
    87.3848007361956, NaN), "CI Lower" = c(4.660160577164, 80.2856274291748, 
    NA), "CI Upper" = c(5.30764252843129, 95.1117110773147, NA
    ), "BSV(CV%)" = c(34.7293553014579, 32.7325901149774, NA), 
        "Shrink(SD)%" = c(38.3888500983383, 45.5419780620688, 
        NA)), class = "data.frame", row.names = c("lCl", "lVc", 
    "prop.err")), omega = structure(c(0.101782141915542, 0, 0, 
    0.1138756892137), .Dim = c(2L, 2L), .Dimnames = list(c("eta.Vc", 
    "eta.Cl"), c("eta.Vc", "eta.Cl"))), time = structure(list(
        saem = 12.67, setup = 0.190357999999988, table = 0.0240000000000009, 
        covariance = 0.0080000000000382, other = 0.549641999999965, 
        logLik = 0.0919999999999845), class = "data.frame", row.names = "elapsed"), 
    objDf = structure(list(OBJF = Inf, AIC = Inf, BIC = Inf, 
        "Log-likelihood" = -Inf, "Condition Number" = 1.83946888191254), row.names = "gauss3_1.6", class = "data.frame"))