expected_values[[runno]] <- list(lik = c(-42575.65, 85169.3, 85230.93), param = c(6.9032,
5.4951, 4.2225, -0.018597, 0.19751), stdev_param = c(0.288, 0.28739,
0.30498, 0.30907, NA), sigma = c(prop.err = 0.19751), parFixedDf = structure(list(
Estimate = c(lVM = 6.90315546765649, lKM = 5.49514317263035,
lVc = 4.22246925793212, lKA = -0.0185967861981011, prop.err = 0.197507782782977
), SE = c(lVM = 0.0302558277223891, lKM = 0.0397233132304445,
lVc = 0.0274659153442656, lKA = 0.0313111512549779, prop.err = NA
), "%RSE" = c(0.438289820708043, 0.722880405160221, 0.650470463288027,
168.368614455411, NA), "Back-transformed" = c(995.410751604438,
243.506387114994, 68.2016840890329, 0.981575067075264, 0.197507782782977
), "CI Lower" = c(938.098669649679, 225.267122548292, 64.6273084608564,
0.92314818062827, NA), "CI Upper" = c(1056.22425067475, 263.22243519174,
71.9737495396016, 1.04369984420928, NA), "BSV(CV%)" = c(29.3423108869783,
31.2213200921692, 29.4079757825884, 31.6598823381821, NA),
"Shrink(SD)%" = c(6.30078108675932, 25.0987494156992, 1.38733991905403,
8.33283368246055, NA)), class = "data.frame", row.names = c("lVM",
"lKM", "lVc", "lKA", "prop.err")), omega = structure(c(0.0829457856277634,
0, 0, 0, 0, 0.082590647364706, 0, 0, 0, 0, 0.0930139845006708,
0, 0, 0, 0, 0.0955236251748349), .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(setup = 0.172772000000138,
optimize = 234.523007, covariance = 234.523009, table = 0.597000000000207,
other = 581.606212), class = "data.frame", row.names = "elapsed"),
objDf = structure(list(OBJF = 72361.5167727051, AIC = 85169.3032778478,
BIC = 85230.9333974314, "Log-likelihood" = -42575.6516389239,
"Condition Number" = 3.00593130680081), row.names = "FOCEi", class = "data.frame"))
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