Parametric bootstrap
Metida.bootstrap
Metida.bootstrap — Functionbootstrap(lmm::LMM; double = false, n = 100, verbose = true, init = lmm.result.theta, rng = default_rng())Parametric bootstrap.
- double - use double approach (default - false);
- n - number of bootstrap samples;
- verbose - show progress bar;
- init - initial values for lmm;
- rng - random number generator.
Parametric bootstrap based on generating random responce vector from known distribution, that given from fitted LMM model.
- Simple bootstrap:
For one-stage bootstrap variance parameters and coefficients simulated in one step.
- Double bootstrap:
For double bootstrap (two-tage) variance parameters simulated in first cycle, than they used for simulating coefficients and var(β) on stage two. On second stage parent-model β used for simulations.
lmm = Metida.LMM(@formula(var~sequence+period+formulation), df0m;
random = Metida.VarEffect(Metida.@covstr(formulation|subject), Metida.CSH),
)
Metida.fit!(lmm)
bt = Metida.bootstrap(lmm; n = 1000, double = true, rng = MersenneTwister(1234))
confint(bt)See also: confint, Metida.miboot, Metida.nvar, Metida.tvar,  Metida.straps, Metida.sdstraps, Metida.thetastraps
Metida.nvar
Metida.nvar — Functionnvar(br::BootstrapResult)Number of coefficient in the model.
Metida.tvar
Metida.tvar — Functiontvar(br::BootstrapResult) = length(br.theta)Number of theta parameters in the model.
Metida.straps
Metida.straps — Functionstraps(br::BootstrapResult, idx::Int)Return coefficients vector.
Metida.sdstraps
Metida.sdstraps — Functionsdstraps(br::BootstrapResult, idx::Int)Return sqrt(var(β)) vector.
Metida.thetastraps
Metida.thetastraps — Functionstraps(br::BootstrapResult, idx::Int)Return theta vector.