proportion: A comprehensive R package for inference on single Binomial proportion and Bayesian computations | Zendy

M.T.R. Subbiah | Zendy; V. Rajeswaran | Zendy

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proportion: A comprehensive R package for inference on single Binomial proportion and Bayesian computations

Author(s) -

M.T.R. Subbiah,

V. Rajeswaran

Publication year - 2017

Publication title -

softwarex

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.528

H-Index - 21

ISSN - 2352-7110

DOI - 10.1016/j.softx.2017.01.001

Subject(s) - frequentist inference , pooling , bayesian probability , computer science , inference , r package , binomial (polynomial) , statistical inference , range (aeronautics) , bayesian inference , binomial proportion confidence interval , econometrics , frequentist probability , statistics , machine learning , negative binomial distribution , artificial intelligence , mathematics , poisson distribution , materials science , composite material

Extensive statistical practice has shown the importance and relevance of the inferential problem of estimating probability parameters in a binomial experiment; especially on the issues of competing intervals from frequentist, Bayesian, and Bootstrap approaches. The package written in the free R environment and presented in this paper tries to take care of the issues just highlighted, by pooling a number of widely available and well-performing methods and apporting on them essential variations. A wide range of functions helps users with differing skills to estimate, evaluate, summarize, numerically and graphically, various measures adopting either the frequentist or the Bayesian paradigm

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