MF: Mitigated Fraction

#' @importFrom methods new setClassUnion setRefClass


setClassUnion("characterORNULL", c("character", "NULL"))
setClassUnion("listORNULL", c("list", "NULL"))
setClassUnion("numericORNULL", c("numeric", "NULL"))
setClassUnion("numericORarray", c("numeric", "array"))
setClassUnion("numericORarrayORtable", c("numeric", "array", "table"))
setClassUnion("numericORinteger", c("numeric", "integer"))

#' @name mf-class
#' @title Class mf
#' @description Parent class for package MF data objects.
#' @docType class
#' @section Fields:
#'
#'   \itemize{
#'
#'   \item{\code{nboot: } }{numeric value specifying number of samples}
#'
#'   \item{\code{alpha: }}{numeric value specifying complement of confidence
#'   interval}
#'
#'   \item{\code{seed: }}{vector of integers specifying seed for pseudo-random
#'   number generator used}
#'
#'   \item{\code{compare: }}{vector of character strings naming groups compared}
#'
#'   \item{\code{rng: }}{character string naming type of random number
#'   generator}
#'
#'   }
#' @keywords documentation
#' @family mf
#' @author \link{MF-package}
mf <- setRefClass("mf", fields = list(nboot = "numeric",
                                      alpha = "numeric",
                                      seed = "numericORinteger",
                                      compare = "character",
                                      rng = "character"))

#' @name mfboot-class
#' @title Class mfboot
#' @description class for data objects produced by MFBoot, contains class mf
#'   with the two additional fields \emph{stat} and \emph{stuff}.
#' @docType class
#' @section Fields:
#'
#'   \itemize{
#'
#'   \item{\code{nboot: } }{numeric value specifying number of samples}
#'
#'   \item{\code{alpha: }}{numeric value specifying complement of confidence
#'   interval}
#'
#'   \item{\code{seed: }}{vector of integers specifying seed for pseudo-random
#'   number generator used}
#'
#'   \item{\code{compare: }}{vector of character strings naming groups compared}
#'
#'   \item{\code{rng: }}{character string naming type of random number
#'   generator}
#'
#'   \item{\code{sample: }}{ what is this?}
#'
#'   \item{\code{stat:} }{matrix of estimates}
#'
#'   }
#' @section Contains: \code{\link{mf-class}}
#' @keywords documentation
#' @family mf
#' @seealso \code{\link{MFBoot}}
#' @author \link{MF-package}
mfboot <- setRefClass("mfboot", contains = "mf",
                      fields = list(stat = "matrix",
                                    sample = "numericORNULL"))

#' @name mfhlboot-class
#' @title Class mfhlboot
#' @description class for data objects produced by HLBoot, contains class mf
#'   with additional fields \emph{MFstat, HLstat, QDIFstat, QXstat, QYstat}
#' @docType class
#' @section Fields:
#'
#'   \itemize{
#'
#'   \item{\code{nboot: } }{Numeric value specifying number of samples.}
#'
#'   \item{\code{alpha: }}{Numeric value specifying complement of confidence
#'   interval.}
#'
#'   \item{\code{seed: }}{Vector of integers specifying seed for pseudo-random
#'   number generator used.}
#'
#'   \item{\code{compare: }}{Vector of character strings naming groups
#'   compared.}
#'
#'   \item{\code{rng: }}{Character string naming type of random number
#'   generator.}
#'
#'   \item{\code{sample: }}{The bootstrapped values.}
#'
#'   \item{\code{MFstat}}{Matrix with columns \emph{observed, median, lower,
#'   upper} for Equal Tailed and Highest Density estimates of mitigated fraction
#'   (MF).}
#'
#'   \item{\code{HLstat}}{Matrix with columns \emph{observed, median, lower,
#'   upper} for Equal Tailed and Highest Density estimates of Hodge-Lehmann
#'   estimator (HL).}
#'
#'   \item{\code{QDIFstat}}{Matrix with columns \emph{observed, median, lower,
#'   upper} for estimates of Quartile Differences.}
#'
#'   \item{\code{QXstat}}{Matrix with columns \emph{observed, median, lower,
#'   upper} for quartiles of treatments, equal tailed.}
#'
#'   \item{\code{QYstat}}{Matrix with columns \emph{observed, median, lower,
#'   upper} for quartiles of response, equal tailed.}
#'
#'   }
#' @section Contains: \code{\link{mf-class}}
#' @keywords documentation
#' @family mf
#' @seealso \code{\link{HLBoot}}
#' @author \link{MF-package}
mfhlboot <- setRefClass("mfhlboot", contains = "mf",
                        fields = list(MFstat = "matrix",
                                      HLstat = "matrix",
                                      QDIFstat = "matrix",
                                      QXstat = "matrix",
                                      QYstat = "matrix",
                                      sample = "listORNULL"))

#' @name mfmp-class
#' @title Class mfmp
#' @description Class mfmp is created from output of function MFmp
#' @docType class
#' @section Fields:
#'
#'   \itemize{
#'
#'   \item{\code{ci:} }{numeric vector of point and interval estimates}
#'
#'   \item{\code{x: } }{numeric vector of length three holding data}
#'
#'   \item{\code{what: }}{text string describing interval type}
#'
#'   \item{\code{alpha: }}{numeric value specifying complement of confidence
#'   interval}
#'
#'   \item{\code{tdist: }}{Logical indicating if t distribution(TRUE) or
#'   gaussian (FALSE)}
#'
#'   \item{\code{df: }}{numeric value indicating degrees freedom}
#'
#'   }
#' @keywords documentation
#' @family mfmp
#' @author \link{MF-package}
#' @seealso \code{\link{MFmp}}
mfmp <- setRefClass("mfmp",
                    fields = list(ci = "numeric",
                                  x = "numericORarrayORtable",
                                  what = "character",
                                  alpha = "numeric",
                                  tdist = "logical",
                                  df = "numeric"))

#' @name mfbootcluster-class
#' @title Class mfbootcluster
#' @description Class mfbootcluster is created from output of function
#'   MFClusBoot
#' @docType class
#' @section Fields:
#'
#'   \itemize{
#'
#'   \item{\code{nboot: } }{numeric value specifying number of samples}
#'
#'   \item{\code{alpha: }}{numeric value specifying complement of confidence
#'   interval}
#'
#'   \item{\code{seed: }}{vector of integers specifying seed for pseudo-random
#'   number generator used}
#'
#'   \item{\code{compare: }}{vector of character strings naming groups compared}
#'
#'   \item{\code{rng: }}{character string naming type of random number
#'   generator}
#'
#'   \item{\code{stat: }}{matrix matrix with columns \emph{observed, median,
#'   lower, upper} for estimates}
#'
#'   \item{\code{what: }}{character vector naming what was resampled:
#'   \emph{clusters}, \emph{units}, \emph{both}}
#'
#'   \item{\code{excludedClusters: }}{character vector naming clusters excluded
#'   because of missing treatment(s)}
#'
#'   \item{\code{call: }}{the call to \code{MFClusBoot}}
#'
#'   \item{\code{sample: }}{what is this?}
#'
#'   \item{\code{All: }}{Field "All" from MFClus call.}
#'
#'   }
#' @section Contains: \code{\link{mf-class}}
#' @keywords documentation
#' @family mf
#' @seealso \code{\link{MFClusBoot}}
#' @author \link{MF-package}
mfbootcluster <- setRefClass("mfbootcluster", contains = "mf",
                             fields = list(stat = "matrix",
                                           what = "character",
                                           excludedClusters = "character",
                                           call = "call",
                                           sample = "numericORNULL",
                                           All = "data.frame"))

#' @name mfcluster-class
#' @title Class mfcluster
#' @description Class mfcluster is created from output of function MFClus
#' @docType class
#' @section Fields:
#'
#'   \itemize{
#'
#'   \item{\code{All: }}{vector with elements:
#'
#'   \itemize{
#'
#'   \item{\emph{w }}{Wilcoxon statistic}
#'
#'   \item{\emph{u }}{Mann-Whitney statistic}
#'
#'   \item{\emph{r }}{mean ridit}
#'
#'   \item{\emph{n1 }}{size of group 1}
#'
#'   \item{\emph{n2 }}{size of group 2}
#'
#'   \item{\emph{mf }}{mitigated fraction}
#'
#'   }}
#'
#'   \item{\code{byCluster: }}{As for All, by clusters}
#'
#'   \item{\code{excludedClusters: }}{character vector naming clusters excluded
#'   because of missing treatment}
#'
#'   \item{\code{call: }}{the call to \code{MFClus}}
#'
#'   \item{\code{compare: }}{character vector naming groups compared}
#'
#'   }
#'
#' @keywords documentation
#' @family mfcluster
#' @seealso \code{\link{MFClus}}
#' @author \link{MF-package}
mfcluster <- setRefClass("mfcluster",
                         fields = list(All = "data.frame",
                                       byCluster = "matrix",
                                       excludedClusters = "characterORNULL",
                                       call = "call",
                                       compare = "character"))

#' @name mfcomponents-class
#' @title Class mfcomponents
#' @description Class mfcomponents is created from output of function MFSubj
#' @docType class
#' @section Fields:
#' \itemize{
#' \item{\code{mf: }}{numeric estimator for mitigated fraction}
#' \item{\code{x: }}{numeric vector containing responses of group 1}
#' \item{\code{y: }}{numeric vector containing responses of group 2}
#' \item{\code{subj: }}{matrix where \code{mf.j} are the subject components}
#' \item{\code{compare: }}{character vector naming groups being compared}
#' }
#' @keywords documentation
#' @family mfcomponents
#' @seealso \code{\link{MFSubj}}
#' @author \link{MF-package}
mfcomponents <- setRefClass("mfcomponents",
                            fields = list(mf = "numeric",
                                          x = "numeric",
                                          y = "numeric",
                                          subj = "matrix",
                                          compare = "character"))

#' @name mfhierdata-class
#' @title Class mfhierdata
#' @description Class mfhierdata is created from output of function MFh
#' @docType class
#' @section Fields:
#'
#'   \itemize{
#'
#'   \item{\code{coreTbl: }}{data.frame with one row for each unique core level
#'   showing values for \code{nx}, \code{ny}, \code{N}, \code{w}, \code{u}, and
#'   median observed response.}
#'
#'   \item{\code{data: }}{data.frame is the restructured input data used for
#'   calculations in MFh and MFnest.}
#'
#'   \item{\code{compare: }}{character vector naming groups being compared.}
#'
#'   \item{\code{formula: }}{formula that was called by user.}
#'
#'   }
#' @keywords documentation
#' @family mfhierdata
#' @seealso \code{\link{MFh}}
#' @author \link{MF-package}
mfhierdata <- setRefClass("mfhierdata",
                          fields = list(coreTbl = "tbl",
                                        data = "tbl",
                                        compare = "character",
                                        formula = "formula"))


#' @name mfclushier-class
#' @title Class mfclushier
#' @description Class mfclushier is created from output of function MFClusHier
#' @docType class
#' @section Fields:
#' \itemize{
#' \item{\code{MFh: }}{output from MFh. A \code{\link{mfhierdata}} object.}
#' \item{\code{MFnest: }}{output from MFnest. A tibble.}
#' }
#' @keywords documentation
#' @family mfclushier
#' @seealso \code{\link{MFh}}, \code{\link{MFnest}}
#' @author \link{MF-package}
mfclushier <- setRefClass("mfclushier", fields = list(MFh = "mfhierdata",
                                                      MFnest = "tbl"))

#' @name mfclusboothier-class
#' @title Class mfclusboothier
#' @description Class mfclusboothier is created from output of function
#' MFClusBootHier.
#' @docType class
#' @section Fields:
#' \itemize{
#' \item{\code{MFhBoot: }}{output from MFhBoot. A list.}
#' \item{\code{MFnestBoot: }}{output from MFnestBoot. A list.}
#' }
#' @keywords documentation
#' @family mfclusboothier
#' @seealso \code{\link{MFhBoot}}, \code{\link{MFnestBoot}}
#' @author \link{MF-package}
mfclusboothier <- setRefClass("mfclusboothier",
                              fields = list(MFhBoot = "list",
                                            MFnestBoot = "list"))