The function which flaremixEM actually calls. This only allows
one barrier constant to be inputted at a time.
try.flare(y, x, lambda = NULL, beta = NULL, sigma = NULL,
alpha = NULL, nu = 1, epsilon = 1e-04,
maxit = 10000, verb = FALSE, restart = 50)try.flare returns a list of class mixEM with items:
The set of predictors (which includes a column of 1's).
The response values.
An nx2 matrix of posterior probabilities for observations.
The final mixing proportions.
The final regression coefficients.
The final standard deviations.
The final exponential rate.
The final log-likelihood.
A vector of each iteration's log-likelihood.
A character vector giving the name of the function.
An n-vector of response values.
An n-vector of predictor values. An intercept term will be added by default.
Initial value of mixing proportions. Entries should sum to 1.
Initial value of beta parameters. Should be a 2x2 matrix where the columns
corresond to the component.
A vector of standard deviations.
A scalar for the exponential component's rate.
A scalar specifying the barrier constant to use.
The convergence criterion.
The maximum number of iterations.
If TRUE, then various updates are printed during each iteration of the algorithm.
The number of times to restart the algorithm in case convergence is not attained. The default is 50.
This usually is not called by the user. The user will likely want flaremixEM, which also
has an example to demonstrate this algorithm.
flaremixEM