bc.fourcomp {bimixt}R Documentation

bc.fourcomp

Description

Implementation of four component model. The four component model estimates an upper and lower component for the cases and an upper and lower component for the controls.

Usage

bc.fourcomp(x.cases, x.controls, lambda.bounds = c(-5, 5), 

start.vals.cases=NULL, start.vals.controls=NULL)

Arguments

x.cases

a numeric vector of case values

x.controls

a numeric vector of control values

lambda.bounds

numeric vector of bounds: c(upper bound, lower bound). Specifies the range for optim to search for the optimization of lambda. Default: c(-5,5).

start.vals.cases

starting values for the EM algorithm for the cases. If NA, the starting values are estimated from the data.

start.vals.controls

starting values for the EM algorithm for the controls. If NA, the starting values are estimated from the data.

Value

lambda

Box-Cox transformation parameter

type

model type ( "4c")

mu.cases

means of the Box-Cox transformed case components

sig.cases

standard deviations of the Box-Cox transformed case components

pi.cases

proportion of cases in each case component

max.loglike.cases

the maximum log likelihood value for the fit of the cases

mu.controls

means of the Box-Cox transformed control components

sig.controls

standard deviations of the Box-Cox transformed control components

pi.controls

proportion of controls in each control component

max.loglike.controls

the maximum log likelihood value for the fit of the controls

max.loglike

the maximum log likelihood value for the model

mu.cases.unt

an estimate of the untransformed means of the case components. Based on Monte Carlo simulations. Values will differ by computer seed.

sig.cases.unt

an estimate of the untransformed standard deviations of the case components. Based on Monte Carlo simulations. Values will differ by computer seed.

mu.controls.unt

an estimate of the untransformed means of the control components. Based on Monte Carlo simulations. Values will differ by computer seed.

sig.controls.unt

an estimate of the untransformed standard deviations of the control components. Based on Monte Carlo simulations. Values will differ by computer seed.

case

original case values

control

original control values

time

running time for the model fit

Author(s)

Michelle Winerip, Garrick Wallstrom, Joshua LaBaer

See Also

bc.binorm bc.twocomp em.twocomp.m1 em.twocomp.m2 em.twocomp.m3


[Package bimixt version 1.0 Index]