Tests of fit for normal inverse Gaussian distributions

DOI10.1016/j.stamet.2009.06.004zbMath1220.62048OpenAlexW2065808663MaRDI QIDQ537399

Simos G. Meintanis, Dimitris Karlis, Konstantinos Fragiadakis

Publication date: 20 May 2011

Published in: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.stamet.2009.06.004

zbMATH Keywords

maximum likelihood estimationcharacteristic functiongoodness-of-fit testparametric bootstrap

Mathematics Subject Classification ID

Related Items (2)

The limit distribution of weighted \(L^2\)-goodness-of-fit statistics under fixed alternatives, with applications ⋮ Estimation of Lévy-driven Ornstein-Uhlenbeck processes: application to modeling of \(\mathrm{CO}_2\) and fuel-switching

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Parametric bootstrap tests for continuous and discrete distributions
• Tests for location-scale families based on the empirical characteristic function
• Goodness-of-fit tests for symmetric stable distributions-empirical characteristic function approach
• Limit behaviour of the empirical characteristic function
• The empirical characteristic function and its applications
• Goodness-of-fit tests for the Cauchy distribution based on the empirical characteristic function
• An EM type algorithm for maximum likelihood estimation of the normal-inverse Gaussian distribution
• Goodness-of-fit tests for the inverse Gaussian distribution based on the empirical Laplace transform
• Bootstrap goodness-of-fit tests with estimated parameters based on empirical transforms
• Non-Gaussian Ornstein–Uhlenbeck-based Models and Some of Their Uses in Financial Economics
• Goodness-of-fit tests for the hyperbolic distribution
• Nonparametric Risk Management With Generalized Hyperbolic Distributions
• Goodness-of-fit testing by transforming to normality: comparison between classical and characteristic function-based methods
• Fibonacci numbers, Lucas numbers and integrals of certain Gaussian processes
• Normal Inverse Gaussian Distributions and Stochastic Volatility Modelling
• On the asymptotic normality of theL₂-Distance Class of Statistics with Estimated Parameters
• Empirical‐distribution‐function goodness‐of‐fit tests for discrete models
• Testing for stability based on the empirical characteristic funstion with applications to financial data
• Apparent scaling
• The bootstrap in econometrics

This page was built for publication: Tests of fit for normal inverse Gaussian distributions