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bimixt (version 1.0)

bc.fourcomp: 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

See Also

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