Usage
lqmmControl(method = "df", LP_tol_ll = 1e-6, LP_tol_theta = 1e-6,
check_theta = FALSE, LP_step = NULL, beta = 0.5, gamma = 1,
reset_step = FALSE, LP_max_iter = 500, UP_tol = 1e-5,
UP_max_iter = 10, startQR = FALSE, verbose = FALSE)
Arguments
method
character vector that specifies the estimation method: "gs" for gradient search and "df" for Nelder-Mead (default).
LP_tol_ll
tolerance expressed as absolute change of the log-likelihood.
LP_tol_theta
tolerance expressed as absolute change of theta
check_theta
logical flag. If TRUE the algorithm performs an additional check on the change in the estimates.
LP_step
step size (default standard deviation of response).
beta
decreasing step factor for line search (0,1).
gamma
nondecreasing step factor for line search (>= 1).
reset_step
logical flag. If TRUE the step size is reset to the initial value at each iteration.
LP_max_iter
maximum number of iterations
UP_tol
tolerance expressed as absolute change of the scale parameter.
UP_max_iter
maximum number of iterations.
startQR
logical flag. If FALSE (default) the least squares estimate of the fixed effects is used as starting value of theta_x and scale. If TRUE the lqm estimate is u