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fitdistrplus : An R Package for Fitting Distributions

Author

Listed:
  • Marie Laure Delignette-Muller

    (Ecologie quantitative et évolutive des communautés [LBBE] - Département écologie évolutive [LBBE] - LBBE - Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - VAS - VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement - CNRS - Centre National de la Recherche Scientifique, LBBE - Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - VAS - VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement - CNRS - Centre National de la Recherche Scientifique)

  • Christophe Dutang

    (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon)

Abstract

The package fitdistrplus provides functions for fitting univariate distributions to different types of data (continuous censored or non-censored data and discrete data) and allowing different estimation methods (maximum likelihood, moment matching, quantile matching and maximum goodness-of-fit estimation). Outputs of fitdist and fitdistcens functions are S3 objects, for which specific methods are provided, including summary, plot and quantile. This package also provides various functions to compare the fit of several distributions to the same data set and can handle to bootstrap parameter estimates. Detailed examples are given in food risk assessment, ecotoxicology and insurance contexts.

Suggested Citation

  • Marie Laure Delignette-Muller & Christophe Dutang, 2015. "fitdistrplus : An R Package for Fitting Distributions," Post-Print hal-01616147, HAL.
    • Handle: RePEc:hal:journl:hal-01616147
    DOI: 10.18637/jss.v064.i04
    Note: View the original document on HAL open archive server: https://hal.science/hal-01616147v1
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