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arXiv · 1602.05885

A Goodness of Fit Test for Non-Gaussian Distributions with Unknown Location and Scale Parameters

Jiwoong Kim
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Abstract

This paper studies computational aspects of an asymptotically distribution-free goodness-of-fit test for non-Gaussian distributions based on the Khmaladze martingale transformation when the location and scale parameters of the distribution are unknown. On top of that, we propose another goodness-of-fit test better than existing one in terms of a statistical power. Simulation studies demonstrate that the proposed test compares favorably with the existing test.

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Jiwoong Kim. 2016-02-18. A Goodness of Fit Test for Non-Gaussian Distributions with Unknown Location and Scale Parameters. https://arxiv.org/abs/1602.05885

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