simplexreg.control {simplexreg} | R Documentation |
Control Parameters for Simplex Regression
Description
Various parameters that control fitting of simplex regression models
using simplexreg
.
Usage
simplexreg.control(maxit = 200, beta = NULL, gamma = NULL, alpha = NULL,
tol = 1e-6, ...)
Arguments
maxit |
maximum number of iterations |
beta |
start value for beta modelling the mean parameter |
gamma |
start value for gamma modelling the dispersion |
alpha |
start value for alpha modelling correlation structure using GEEs, see Song et.al (2004) |
tol |
numeric tolerance for convergence in Fisher scoring |
... |
currently not used |
Value
A list with the arguments specified.
See Also
Examples
# GLM models
data("sdac", package = "simplexreg")
sim.glm1 <- simplexreg(rcd~ageadj+chemo, link = "logit",
data = sdac, beta = c(1.115, 0.013, 0.252))
sim.glm2 <- simplexreg(rcd~ageadj+chemo|age, link = "logit",
data = sdac, beta = c(1.115, 0.013, 0.252), gamma = c(2.61, -0.015))
# GEE models
data("retinal", package = "simplexreg")
sim.gee1 <- simplexreg(Gas~LogT+LogT2+Level|1|Time, link = "logit",
corr = "Exc", id = ID, data = retinal, beta = c(2.72, 0.034, -0.329, 0.409),
alpha = -0.3)
sim.gee2 <- simplexreg(Gas~LogT+LogT2+Level|LogT+Level|Time,
link = "logit", corr = "AR1", id = ID, data = retinal, alpha = -0.3,
beta = c(2.72, 0.034, -0.329, 0.409))
[Package simplexreg version 1.3 Index]