## Abstract

A routine was developed to fit probability distribution functions to data, using the maximum likelihood method. The distributions that can be fitted include the Gaussian (normal), two-parameter log Gaussian (log normal), three-parameter log Gaussian, exponential, shifted exponential, beta, gamma, three-parameter gamma (Pearson type III), log gamma (log Pearson type III), inverted gamma (Pearson type V), Gumbel (extreme value type I) for minima, Gumbel (extreme value type I) for maxima, Frechet (extreme value type II) for minima, Frechet (extreme value type II) for maxima, three-parameter Frechet for maxima; Weibull (extreme value type III) for maxima, Weibull (extreme value type III) for minima, and three-parameter Weibull for minima distributions. Test statistics are provided for the chi-square, Kolmogorov-Smirnov, Kuiper, Cramer-von Mises, Anderson-Darling, and maximum likelihood goodness-of-fit tests. Graphs of the frequency histogram with the fitted probability distribution function superimposed, and of the empirical distribution function for the sample data, together with the fitted cumulative density function, are provided for visual assessment.

Original language | English (US) |
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Pages (from-to) | 401-408 |

Number of pages | 8 |

Journal | Applied Engineering in Agriculture |

Volume | 9 |

Issue number | 4 |

State | Published - Jul 1993 |

Externally published | Yes |

## ASJC Scopus subject areas

- Agricultural and Biological Sciences (miscellaneous)