Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Abu Bakar, Shaiful Anuar, Nadarajah, Saralees, ABSL Kamarul Adzhar, Zahrul Azmir, Mohamed, Ibrahim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4896504/
https://www.ncbi.nlm.nih.gov/pubmed/27272043
http://dx.doi.org/10.1371/journal.pone.0156537
_version_ 1782436028540256256
author Abu Bakar, Shaiful Anuar
Nadarajah, Saralees
ABSL Kamarul Adzhar, Zahrul Azmir
Mohamed, Ibrahim
author_facet Abu Bakar, Shaiful Anuar
Nadarajah, Saralees
ABSL Kamarul Adzhar, Zahrul Azmir
Mohamed, Ibrahim
author_sort Abu Bakar, Shaiful Anuar
collection PubMed
description 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.
format Online
Article
Text
id pubmed-4896504
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-48965042016-06-16 Gendist: An R Package for Generated Probability Distribution Models Abu Bakar, Shaiful Anuar Nadarajah, Saralees ABSL Kamarul Adzhar, Zahrul Azmir Mohamed, Ibrahim PLoS One Research Article 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 2016-06-07 /pmc/articles/PMC4896504/ /pubmed/27272043 http://dx.doi.org/10.1371/journal.pone.0156537 Text en © 2016 Abu Bakar et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Abu Bakar, Shaiful Anuar
Nadarajah, Saralees
ABSL Kamarul Adzhar, Zahrul Azmir
Mohamed, Ibrahim
Gendist: An R Package for Generated Probability Distribution Models
title Gendist: An R Package for Generated Probability Distribution Models
title_full Gendist: An R Package for Generated Probability Distribution Models
title_fullStr Gendist: An R Package for Generated Probability Distribution Models
title_full_unstemmed Gendist: An R Package for Generated Probability Distribution Models
title_short Gendist: An R Package for Generated Probability Distribution Models
title_sort gendist: an r package for generated probability distribution models
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4896504/
https://www.ncbi.nlm.nih.gov/pubmed/27272043
http://dx.doi.org/10.1371/journal.pone.0156537
work_keys_str_mv AT abubakarshaifulanuar gendistanrpackageforgeneratedprobabilitydistributionmodels
AT nadarajahsaralees gendistanrpackageforgeneratedprobabilitydistributionmodels
AT abslkamaruladzharzahrulazmir gendistanrpackageforgeneratedprobabilitydistributionmodels
AT mohamedibrahim gendistanrpackageforgeneratedprobabilitydistributionmodels