2003•Communications in Statistics - Simulation and ComputationRequires access

Exact EDF Goodness-of-Fit Tests for Inverse Gaussian Distributions

Truc Thanh Nguyen, Khoan T. Dinh

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Abstract

Exact EDF goodness-of-fit tests for inverse Gaussian (m, λ) distributions in different cases of unknown parameters are constructed. In the case m is unknown and λ is known, a chi-square test is also proposed. The powers of the tests are estimated by Monte Carlo method at several different alternative distributions.

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What this paper is about

Exact EDF goodness-of-fit tests for inverse Gaussian (m, λ) distributions in different cases of unknown parameters are constructed. In the case m is unknown and λ is known, a chi-square test is also proposed. The powers of the tests are estimated by Monte Carlo method at several different alternative distributions.

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Available abstract

Exact EDF goodness-of-fit tests for inverse Gaussian (m, λ) distributions in different cases of unknown parameters are constructed. In the case m is unknown and λ is known, a chi-square test is also proposed. The powers of the tests are estimated by Monte Carlo method at several different alternative distributions.

Key concepts: Goodness of fit, Inverse Gaussian distribution, Inverse, Monte Carlo method, Gaussian, Mathematics, Applied mathematics, Statistics

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