Distrubtion function devined by: alpha*Normal(mean, varience)+(1-alpha) *Exponential(lambda).

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`xi` |
A vector of observations, assumed to be real numbers in the inveraval (-Inf,+Inf). |

`wi` |
A vector of weights. Default: vector of repeating 1; indicating all observations are weighted equally. (Are these normalized internally?! Or do they have to be [0,1]?) |

`guess` |
Initial guess for paremeters. Default: c(0.5, 0, 1, 1). |

`tol` |
Convergence tolerance. Default: sqrt(.Machine$double.eps). |

`maxit` |
Maximum number of iterations. Default: 10,000. |

Fits nicely with data types that look normal overall, but have a long tail starting for positive values.

Returns a list of parameters for the best-fit normal distribution (alpha, mean, varience, and lambda).

Charles G. Danko

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