Visualization and Analysis of Statistical Measures of Confidence
c(person("Christopher", "Weld", role = c("aut", "cre"), email = "ceweld@email.wm.edu", comment = c(ORCID = "0000-0001-5902-9738")),
person("Hayeon", "Park", role = "aut"),
person("Lawrence", "Leemis", role = "aut"),
person("Andrew", "Loh", role = "ctb"),
person("Yuan", "Chang", role = "ctb"),
person("Brock", "Crook", role = "ctb"),
person("Xin", "Zhang", role = "ctb"))
Enables: (1) plotting two-dimensional confidence regions, and (2) calculating
confidence intervals and the associated actual coverage for binomial proportions.  Both
are given in greater detail next. (1) Plots the two-dimensional confidence region for
probability distribution parameters (supported distribution suffixes: gamma, invgauss,
lnorm, llogis, norm, weibull) corresponding to a user given dataset and level of
significance. The crplot() algorithm plots more points in areas of greater curvature to
ensure a smooth appearance throughout the confidence region boundary.  An alternative
heuristic plots a specified number of points at roughly uniform intervals along its
boundary.  Both heuristics build upon the radial profile log-likelihood ratio technique
for plotting two-dimensional confidence regions given by Jaeger (2016)
<doi:10.1080/00031305.2016.1182946>. (2) Calculates confidence interval bounds for a
binomial proportion with binomTest(), calculates the actual coverage with
binomTestCoverage(), and plots the actual coverage with binomTestCoveragePlot(). Calculates
confidence interval bounds for the binomial proportion using an ensemble of constituent
confidence intervals with binomTestEnsemble().
Christopher Weld [aut, cre] (<https://orcid.org/0000-0001-5902-9738>),
Hayeon Park [aut],
Lawrence Leemis [aut],
Andrew Loh [ctb],
Yuan Chang [ctb],
Brock Crook [ctb],
Xin Zhang [ctb]

graphics, stats, statmod, STAR, SDMTools
Enables: (1) plotting two-dimensional confidence regions, and (2) calculating
confidence intervals and the associated actual coverage for binomial proportions.  Both
are given in greater detail next. (1) Plots the two-dimensional confidence region for
probability distribution parameters (supported distribution suffixes: gamma, invgauss,
llogis, lnorm, norm, unif, weibull) corresponding to a user given dataset and level of
significance. The crplot() algorithm plots more points in areas of greater curvature to
ensure a smooth appearance throughout the confidence region boundary.  An alternative
heuristic plots a specified number of points at roughly uniform intervals along its
boundary.  Both heuristics build upon the radial profile log-likelihood ratio technique
for plotting two-dimensional confidence regions given by Jaeger (2016)
<doi:10.1080/00031305.2016.1182946>. (2) Calculates confidence interval bounds for a
binomial proportion with binomTest(), calculates the actual coverage with
binomTestCoverage(), and plots the actual coverage with binomTestCoveragePlot(). Calculates
confidence interval bounds for the binomial proportion using an ensemble of constituent
confidence intervals with binomTestEnsemble().