Goodness of Fit Tests for Some Generalized Distributions
| dc.contributor.author | Omekam, Ifeyinwa | |
| dc.contributor.author | Adejumo, Adebowale | |
| dc.date.accessioned | 2023-06-27T10:17:55Z | |
| dc.date.available | 2023-06-27T10:17:55Z | |
| dc.date.issued | 2020-04 | |
| dc.description.abstract | Analysis of data without a pre-knowledge of the distribution that describes data may lead to misleading or irrelevant result. Distribution fitting to data often lead to the selection of the best fitting distribution for data analysis. In this article, some existing distributions are fitted to Maternal Mortality Ratio (MMR) data. Using the best fitting distribution obtained as base distribution, generalized distributions having additional parameters are then derived and subsequently fitted to MMR to assess goodness of fit. Generalized distributions improved goodness of fit. | en_US |
| dc.identifier.citation | Omekam I.V. and Adejumo A.O. (2020). Goodness of Fit Tests for Some Generalized Distributions. FUW Trends in Science & Technology Journal. 5(1): 241-246. Published by Federal University Wukari, Taraba State, Nigeria | en_US |
| dc.identifier.issn | 24085162 | |
| dc.identifier.issn | 20485170 | |
| dc.identifier.uri | https://uilspace.unilorin.edu.ng/handle/20.500.12484/11350 | |
| dc.language.iso | en | en_US |
| dc.publisher | Federal University Wukari, Taraba State, Nigeria | en_US |
| dc.subject | Goodness of fit; Lehmann alternatives, Marshall, Olkin methods | en_US |
| dc.title | Goodness of Fit Tests for Some Generalized Distributions | en_US |
| dc.type | Article | en_US |
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