expected_values[[runno]] <- list(lik = c(-13379.95, 26777.9, 26829.49), param = c(1.3707,
4.2365, 1.3796, 3.944, 0.20389), stdev_param = c(0.3083, 0.27919,
0.37856, 0.44038, NA), sigma = c(prop.err = 0.20389), parFixedDf = structure(list(
Estimate = c(lCl = 1.37068942165859, lVc = 4.23650378882907,
lQ = 1.37956080020267, lVp = 3.94402910133741, prop.err = 0.203888420582905
), SE = c(lCl = 0.0269359436325397, lVc = 0.0331615030704903,
lQ = 0.0978933689291964, lVp = 0.0512013870365352, prop.err = NA
), "%RSE" = c(1.96513836080723, 0.782756365235207, 7.095980758138,
1.29820003151531, NA), "Back-transformed" = c(3.93806474692949,
69.1656110410504, 3.97315623482168, 51.6261899728662, 0.203888420582905
), "CI Lower" = c(3.73555328286276, 64.8131449619857, 3.27950771019393,
46.6968274084222, NA), "CI Upper" = c(4.15155474348472, 73.81036290536,
4.81351832692258, 57.0759008487538, NA), "BSV(CV%)" = c(28.472129517171,
31.5777334279218, 46.2620141336253, 39.2537930815598, NA),
"Shrink(SD)%" = c(-0.353655841428813, 9.26623815689328, 52.2043439693742,
26.3701519427173, NA)), class = "data.frame", row.names = c("lCl",
"lVc", "lQ", "lVp", "prop.err")), omega = structure(c(0.0950513507150469,
0, 0, 0, 0, 0.0779477911051127, 0, 0, 0, 0, 0.143308712212964,
0, 0, 0, 0, 0.193935021340231), .Dim = c(4L, 4L), .Dimnames = list(
c("eta.Vc", "eta.Cl", "eta.Vp", "eta.Q"), c("eta.Vc", "eta.Cl",
"eta.Vp", "eta.Q"))), time = structure(list(setup = 0.23942300000008,
optimize = 147.215127, covariance = 147.215144, table = 0.127999999999702,
other = 287.466306), class = "data.frame", row.names = "elapsed"),
objDf = structure(list(OBJF = 22569.5436234205, AIC = 26777.9033348338,
BIC = 26829.4907113314, "Log-likelihood" = -13379.9516674169,
"Condition Number" = 14.1906451776051), row.names = "FOCEi", class = "data.frame"))
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