lqmmControl: Control parameters for lqmm estimation

View source: R/lqmm.R

lqmmControlR Documentation

Control parameters for lqmm estimation

Description

A list of parameters for controlling the fitting process.

Usage

lqmmControl(method = "gs", LP_tol_ll = 1e-5, LP_tol_theta = 1e-5,
	check_theta = FALSE, LP_step = NULL, beta = 0.5, gamma = 1,
	reset_step = FALSE, LP_max_iter = 500, UP_tol = 1e-4,
	UP_max_iter = 20, startQR = FALSE, verbose = FALSE)

Arguments

method

character vector that specifies the estimation method: "gs" for gradient search (default) and "df" for Nelder-Mead.

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 used.

verbose

logical flag.

Details

LP (lower loop) refers to the estimation of regression coefficients and variance-covariance parameters. UP (upper loop) refers to the estimation of the scale parameter.

Value

a list of control parameters.

Author(s)

Marco Geraci

See Also

lqmm


lqmm documentation built on April 6, 2022, 5:09 p.m.