goft

R package goft: Tests of Fit for some Probability Distributions. Goodness-of-fit tests for gamma, inverse Gaussian, log-normal, ’Weibull’, ’Frechet’, Gumbel, normal, multivariate normal, Cauchy, Laplace or double exponential, exponential and generalized Pareto distributions. Parameter estimators for gamma, inverse Gaussian and generalized Pareto distributions.

Keywords for this software

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References in zbMATH (referenced in 5 articles , 1 standard article )

Showing results 1 to 5 of 5.
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  1. Azaïs, R.; Ferrigno, S.; Martinez, M.-J.: cvmgof: an R package for Cramér-von Mises goodness-of-fit tests in regression models (2022)
  2. Chaturvedi, Ajit; Bapat, Sudeep R.; Joshi, Neeraj: Sequential estimation of an inverse Gaussian mean with known coefficient of variation (2022)
  3. Justine Lequesne, Philippe Regnault: vsgoftest: An R Package for Goodness-of-Fit Testing Based on Kullback-Leibler Divergence (2020) not zbMATH
  4. Jana, Nabakumar; Kumar, Somesh: Ordered classification rules for inverse Gaussian populations with unknown parameters (2019)
  5. González-Estrada, E.; Villaseñor, J. A.: An R package for testing goodness of fit: goft (2018)