expected_values[[runno]] <- list(lik = c(-30891.66, 61801.33, 61859.39), param = c(7.0749,
6.0732, 4.1774, -0.1469, 0.19971), stdev_param = c(0.28935, 0.2065,
0.66994, 0.42287, NA), sigma = c(prop.err = 0.19971), parFixedDf = structure(list(
Estimate = c(lVM = 7.07493269744214, lKM = 6.07319376865854,
lVc = 4.17741760393196, lKA = -0.146903921479333, prop.err = 0.199707385692132
), SE = c(lVM = 0.0346115842770815, lKM = 0.0993207366092986,
lVc = 0.0283234622314695, lKA = 0.0601715193636507, prop.err = NA
), "%RSE" = c(0.489214325524184, 1.63539548370505, 0.678013665782668,
40.9597774911107, NA), "Back-transformed" = c(1181.96394893054,
434.064772631269, 65.1972704590941, 0.863376925409267, 0.199707385692132
), "CI Lower" = c(1104.44170155653, 357.283184770414, 61.6766020675023,
0.767330299335004, NA), "CI Upper" = c(1264.92758703568,
527.347031348555, 68.9189081892689, 0.971445694214299, NA
), "BSV(CV%)" = c(20.8723365876416, 75.2632786411224, 29.5518489877306,
44.250350531208, NA), "Shrink(SD)%" = c(32.3979657686679,
26.7891673763404, 4.29465160053977, 36.7081092126977, NA)), class = "data.frame", row.names = c("lVM",
"lKM", "lVc", "lKA", "prop.err")), omega = structure(c(0.0837262331799096,
0, 0, 0, 0, 0.0426431609138547, 0, 0, 0, 0, 0.448815813897369,
0, 0, 0, 0, 0.178823238318411), .Dim = c(4L, 4L), .Dimnames = list(
c("eta.Vc", "eta.VM", "eta.KM", "eta.KA"), c("eta.Vc", "eta.VM",
"eta.KM", "eta.KA"))), time = structure(list(saem = 379.746,
setup = 0.16508499999984, table = 0.338999999999942, cwres = 0.559000000000196,
covariance = 0.170999999999822, other = 0.368915000000698), class = "data.frame", row.names = "elapsed"),
objDf = structure(list(OBJF = 53182.0649875507, AIC = 61801.3296583465,
BIC = 61859.3891388467, "Log-likelihood" = -30891.6648291732,
"Condition Number" = 14.6315597373658), row.names = "FOCEi", class = "data.frame"))
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