Package: conf
Type: Package
Title: Visualization and Analysis of Statistical Measures of Confidence
Version: 1.7.0
Authors@R: 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("Kexin", "Feng", role = "aut"),
  person("Heather", "Sasinowska", 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")) 
Maintainer: Christopher Weld <ceweld@email.wm.edu>
Imports: graphics, stats, statmod, STAR, fitdistrplus, pracma,
        rootSolve, utils
Description: Enables: (1) plotting two-dimensional confidence regions, (2) coverage analysis
  of confidence region simulations and (3) calculating confidence intervals and the associated 
  actual coverage for binomial proportions. Each is given in greater detail next. 
  (1) Plots the two-dimensional confidence region for probability distribution parameters 
  (supported distribution suffixes: cauchy, gamma, invgauss, logis, llogis, lnorm, norm, unif, 
  weibull) corresponding to a user-given complete or right-censored 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 
  confidence regions given by Jaeger (2016) <doi:10.1080/00031305.2016.1182946>, and
  are detailed in a publication by Weld (2019) <doi:10.1080/00031305.2018.1564696>. 
  (2) Performs confidence region coverage simulations for a random sample drawn from a user-
  specified parametric population distribution, or for a user-specified dataset and point of 
  interest with coversim(). (3) 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(). Calculates confidence interval bounds for the binomial proportion using 
  a complete enumeration of all possible transitions from one actual coverage acceptance curve 
  to another which minimizes the root mean square error for n <= 15 and follows the transitions 
  for well-known confidence intervals for n > 15 using binomTestMSE().
Depends: R (>= 3.2.0)
License: GPL (<= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-08-15 02:50:58 UTC; christopherweld
Author: Christopher Weld [aut, cre] (<https://orcid.org/0000-0001-5902-9738>),
  Hayeon Park [aut],
  Kexin Feng [aut],
  Heather Sasinowska [aut],
  Lawrence Leemis [aut],
  Andrew Loh [ctb],
  Yuan Chang [ctb],
  Brock Crook [ctb],
  Xin Zhang [ctb]
Repository: CRAN
Date/Publication: 2020-08-24 14:30:08 UTC
Built: R 4.0.5; ; 2022-04-21 07:26:17 UTC; windows
