simplexreg.control: Control Parameters for Simplex Regression

In simplexreg: Regression Analysis of Proportional Data Using Simplex Distribution

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

simplexreg

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))

simplexreg documentation built on May 1, 2019, 7:12 p.m.