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bimixt (version 1.0)

bc.twocomp: bc.twocomp

Description

Implementation of two component models. In the two component unconstrained model, the components of the control and case mixtures are the same; however the mixture probabilities may differ for cases and controls. In the two component constrained model, all controls are distributed according to one of the two components while cases follow a mixture distribution of the two components.

Usage

bc.twocomp(x.cases, x.controls, constrained = T, lambda.bounds = c(-5, 5),


control.comp = 1, start.vals=NULL)

Arguments

x.cases
a numeric vector of case values
x.controls
a numeric vector of control values
constrained
Boolean indicating whether the two component constrained model should be used (default T) or the two component unconstrained model should be used (F)
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).
control.comp
indicator of which component contains the controls (1 or 2)
start.vals
starting values for the EM algorithm. If NA, the starting values are estimated from the data.

Value

lambda
Box-Cox transformation parameter
type
model type ( "2cc" or "2cu")
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
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 (always equal to 1 for 2cc since all controls are forced into one component)
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.fourcomp em.twocomp.m1 em.twocomp.m2 em.twocomp.m3