Simulation estimation of goodness-of-fit test for right skewed distributions

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dc.contributor.authorElobaid, Rafida M.
dc.contributor.authorElshareif, Elgilani
dc.date.accessioned2020-03-01T06:48:19Z
dc.date.available2020-03-01T06:48:19Z
dc.date.copyright2017
dc.date.issued2017
dc.descriptionThis article is licensed under Creative Commons License and full text is openly accessible in CUD Digital Repository. The version of the scholarly record of this article is published in Asian Journal of Scientific Research (2017), accessible online through this link https://doi.org/10.3923/ajsr.2017.56.59.en_US
dc.description.abstractObjective: This study derives a goodness-of-fit test based on chi-square statistic using simulation and examines the values of the χ2 test statistic behavior with the level of skewness for two different distributions, namely chi-square and inverse Gaussian. Methodology: For this purpose, simulation estimation was conducted to generate random numbers from different skewed distributions. Different sample sizes and skewness values were considered and the corresponding values of the χ2 test statistic were derived. Results: The results show a statistically significant evidence for an inverse relationship between the value of χ2 test and the level of skewness for all distributions, i.e. the value of χ2 test statistic decreases as the value of skewness increases and vice versa. The research results also show that the method, estimation by simulation, produces an estimator which is shown to have asymptotic assumed distribution with large sample size. Conclusion: These results are relevant to theories in which shape and skewness measure can be used to determine the validity of the assumed right skewed distribution to fit the data well. The results also have practical implications for portfolio managers who are managing funds to optimize risk-adjusted performance and individual investors who prefer positive skewness in rates of return. © 2017 Rafida M. Elobaid and Elgilani Elshareif.en_US
dc.identifier.citationElobaid, R. M., & Elshareif, E. (2017). Simulation estimation of goodness-of-fit test for right skewed distributions. Asian Journal of Scientific Research, 10(1), 56–59. https://doi.org/10.3923/ajsr.2017.56.59en_US
dc.identifier.issn19921454
dc.identifier.urihttp://dx.doi.org/10.3923/ajsr.2017.56.59
dc.identifier.urihttp://hdl.handle.net/20.500.12519/180
dc.language.isoenen_US
dc.publisherAsian Network for Scientific Informationen_US
dc.relationAuthors Affiliations: Elobaid, R.M., Department of General Science, Prince Sultan University, Saudi Arabia; Elshareif, E., School of Graduate Studies, Canadian University, Dubai, United Arab Emirates
dc.relation.ispartofseriesAsian Journal of Scientific Research;Vol. 10, no. 1
dc.rightsThis is an open access article distributed under the terms of the creative commons attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.
dc.rights.holderCopyright : 2017 Rafida M. Elobaid and Elgilani Elshareif
dc.subjectChi-square test statisticen_US
dc.subjectGoodness-of-fit testen_US
dc.subjectInverse Gaussian distributionen_US
dc.subjectRight skewed distributionsen_US
dc.subjectShape parameteren_US
dc.subjectSimulationen_US
dc.subjectSkewness measureen_US
dc.subjectχ2 distributionen_US
dc.titleSimulation estimation of goodness-of-fit test for right skewed distributionsen_US
dc.typeArticleen_US

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