R: Mixtures of Regressions with Flare MM Algorithm

try.flare {mixtools} | R Documentation

## Mixtures of Regressions with Flare MM Algorithm

### Description

The function which `flaremixEM` actually calls. This only allows one barrier constant to be inputted at a time.

### Usage

    try.flare(y, x, lambda = NULL, beta = NULL, sigma = NULL,
              alpha = NULL, nu = 1, epsilon = 1e-04,
              maxit = 10000, verb = FALSE, restart = 50)

### Arguments

`y` | An n-vector of response values.
`x` | An n-vector of predictor values. An intercept term will be added by default.
`lambda` | Initial value of mixing proportions. Entries should sum to 1.
`beta` | Initial value of `beta` parameters. Should be a 2x2 matrix where the columns corresond to the component.
`sigma` | A vector of standard deviations.
`alpha` | A scalar for the exponential component's rate.
`nu` | A scalar specifying the barrier constant to use.
`epsilon` | The convergence criterion.
`maxit` | The maximum number of iterations.
`verb` | If TRUE, then various updates are printed during each iteration of the algorithm.
`restart` | The number of times to restart the algorithm in case convergence is not attained. The default is 50.

### Details

This usually is not called by the user. The user will likely want `flaremixEM`, which also has an example to demonstrate this algorithm.

### Value

`try.flare` returns a list of class `mixEM` with items:

`x` | The set of predictors (which includes a column of 1's).
`y` | The response values.
`posterior` | An nx2 matrix of posterior probabilities for observations.
`lambda` | The final mixing proportions.
`beta` | The final regression coefficients.
`sigma` | The final standard deviations.
`alpha` | The final exponential rate.
`loglik` | The final log-likelihood.
`all.loglik` | A vector of each iteration's log-likelihood.
`ft` | A character vector giving the name of the function.

### See Also

`flaremixEM`

[Package mixtools version 1.2.0 Index]