Gendist: An R package for generated probability distribution models
In this paper, we introduce the R package gendist that computes the probability density function, the cumulative distribution function, the quantile function and generates random values for several generated probability distribution models including the mixture model, the composite model, the folded...
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my.um.eprints.184452017-12-05T03:23:31Z http://eprints.um.edu.my/18445/ Gendist: An R package for generated probability distribution models Bakar, S.A.A. Nadarajah, S. Kamarul Adzhar, Z.A.A. Mohamed, I. Q Science (General) QA Mathematics In this paper, we introduce the R package gendist that computes the probability density function, the cumulative distribution function, the quantile function and generates random values for several generated probability distribution models including the mixture model, the composite model, the folded model, the skewed symmetric model and the arc tan model. These models are extensively used in the literature and the R functions provided here are flexible enough to accommodate various univariate distributions found in other R packages. We also show its applications in graphing, estimation, simulation and risk measurements. Public Library of Science 2016 Article PeerReviewed Bakar, S.A.A. and Nadarajah, S. and Kamarul Adzhar, Z.A.A. and Mohamed, I. (2016) Gendist: An R package for generated probability distribution models. PLoS ONE, 11 (6). e0156537. ISSN 1932-6203 https://doi.org/10.1371/journal.pone.0156537 doi:10.1371/journal.pone.0156537 |
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Q Science (General) QA Mathematics Bakar, S.A.A. Nadarajah, S. Kamarul Adzhar, Z.A.A. Mohamed, I. Gendist: An R package for generated probability distribution models |
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In this paper, we introduce the R package gendist that computes the probability density function, the cumulative distribution function, the quantile function and generates random values for several generated probability distribution models including the mixture model, the composite model, the folded model, the skewed symmetric model and the arc tan model. These models are extensively used in the literature and the R functions provided here are flexible enough to accommodate various univariate distributions found in other R packages. We also show its applications in graphing, estimation, simulation and risk measurements. |
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Article |
author |
Bakar, S.A.A. Nadarajah, S. Kamarul Adzhar, Z.A.A. Mohamed, I. |
author_facet |
Bakar, S.A.A. Nadarajah, S. Kamarul Adzhar, Z.A.A. Mohamed, I. |
author_sort |
Bakar, S.A.A. |
title |
Gendist: An R package for generated probability distribution models |
title_short |
Gendist: An R package for generated probability distribution models |
title_full |
Gendist: An R package for generated probability distribution models |
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Gendist: An R package for generated probability distribution models |
title_full_unstemmed |
Gendist: An R package for generated probability distribution models |
title_sort |
gendist: an r package for generated probability distribution models |
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Public Library of Science |
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2016 |
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http://eprints.um.edu.my/18445/ https://doi.org/10.1371/journal.pone.0156537 |
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1643690707932676096 |