hopit modelAn auxiliary function for controlling the fitting of a hopit model.
Use this function to set the control
parameters of the hopit and other related functions.
hopit.control(
grad.eps = 3e-05,
bgfs.maxit = 10000,
cg.maxit = 10000,
nlm.maxit = 150,
bgfs.reltol = 5e-10,
cg.reltol = 5e-10,
nlm.gradtol = 1e-07,
nlm.steptol = 1e-07,
fit.methods = "BFGS",
nlm.fit = FALSE,
trace = TRUE,
transform.latent = "none",
transform.thresh = "none"
)an epsilon parameter ("a very small number") used to calculate the Hessian from the gradient function.
the maximum number of iterations.
See optim and nlm for details.
the relative convergence tolerances for the BFGS and the CG methods.
See optim for details.
a tolerance at which the scaled gradient is
considered close enough to zero and
a minimum allowable relative step length for the nlm method. See nlm.
"CG", "BFGS", or both. If both, the CG is run first, followed by the BFGS. See optim.
a logical; if FALSE (default) the nlm optimization method
is omitted and only the BFGS and/or the CG methods are run.
a logical for whether to trace the process of model fitting.
a type of transformation applied to the all of the latent's or all of the threshold's numeric variables. Possible values:
"none" : no transformation
"min" : subtract the minimum from a variable
"scale_01" : transform the variable to fit the range from 0 to 1
"standardize" or "standardise" : subtract the mean from a variable then divide it by its standard deviation
"standardize_trunc" or "standardise_trunc" : subtract the minimum from a variable then divide it by its standard deviation
Maciej J. Danko
hopit