Testing the Fit of Gamma Distributions Using the Empirical Moment Generating Function

DOI10.1080/03610920500476424zbMath1084.62016OpenAlexW2126166398MaRDI QIDQ5201512

Ioannis A. Koutrouvelis, George C. Canavos, Athanasios G. Kallioras

Publication date: 19 April 2006

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610920500476424

zbMATH Keywords

tablesgoodness-of-fittwo-parameter gamma distributionempirical moment generating functionthree-parameter gamma distributionminimum chi-squared tests

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Parametric hypothesis testing (62F03) Monte Carlo methods (65C05)

Related Items (11)

On Generalized Tests of Fit for Multinomial Populations ⋮ On a test of normality based on the empirical moment generating function ⋮ A note on using the empirical moment generating function to estimate the variance of nonparametric trend estimates from independent time series replicates ⋮ Normality testing for a long-memory sequence using the empirical moment generating function ⋮ Testing skew normality via the moment generating function ⋮ Cumulant Plots for Assessing the Gamma Distribution ⋮ Goodness-of-Fit Tests for the Gamma Distribution Based on the Empirical Laplace Transform ⋮ A new characterization of the Gamma distribution and associated goodness-of-fit tests ⋮ Graphical procedures and goodness-of-fit tests for the compound poisson-exponential distribution ⋮ Smooth tests for the gamma distribution ⋮ Goodness-of-Fit Tests for Bivariate and Multivariate Skew-Normal Distributions

Cites Work

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• A test for the composite hypothesis that a population has a gamma distribution
• Estimating Mixtures of Normal Distributions and Switching Regressions
• Estimation in the three-parameter gamma distribution based on the empirical moment generation function
• Theory & Methods: Estimating the parameters of Poisson‐exponential models
• Discrimination between the Log-Normal and the Weibull Distributions

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