#' @title R6 Sample Quantiles
#' @name SampleQuantiles
#' @description The R6 class \code{SampleQuantiles} produces the sample
#' quantiles corresponding to the given probabilities. It uses
#' \link[stats]{quantile} from the package \pkg{stats}.
#' @param x An \code{R} object. Currently there are methods for numeric vectors
#' @param na.rm a logical value indicating whether \code{NA} values should be
#' stripped before the computation proceeds.
#' @param digits integer indicating the number of decimal places to be used.
#' @param probs numeric vector of probabilities with values in \code{[0,1]}.
#' @param names logical; if TRUE, the result has a \link[base]{names} attribute
#' regarding the percentiles.
#' @param type an integer between 1 and 9 selecting one of the nine quantile
#' algorithms explained in \link[stats]{quantile} to be used.
#' @examples
#' x <- c(
#' 0.2, 0.5, 1.1, 1.4, 1.8, 2.3, 2.5, 2.7, 3.5, 4.4,
#' 4.6, 5.4, 5.4, 5.7, 5.8, 5.9, 6.0, 6.6, 7.1, 7.9
#' )
#' SampleQuantiles$new(x)$qx()
#' percentile_95 <- SampleQuantiles$new(x, na.rm = TRUE, digits = 2, probs = 0.95)
#' percentile_95$qx()
#' percentile_75 <- SampleQuantiles$new(x, na.rm = TRUE, digits = 3, probs = 0.75)
#' percentile_75$qx()
#' R6::is.R6(percentile_95)
#' @export
#' @import dplyr SciViews boot R6 utils
NULL
#' @importFrom stats quantile sd qchisq qnorm
#' @importFrom MBESS conf.limits.nct
NULL
SampleQuantiles <- R6::R6Class(
classname = "SampleQuantiles",
public = list(
# ---------------- determining defaults for arguments -----------------
x = NA,
na.rm = FALSE,
digits = 1,
probs = 0.5,
names = TRUE,
type = 7,
eps = NA,
epsp1 = NA,
epsm1 = NA,
# --------- determining constructor defaults for arguments ------------
initialize = function(
x = NA,
na.rm = FALSE,
digits = 1,
probs = 0.5,
names = TRUE,
type = 7,
...) {
# ----------------------- check NA or NAN -------------------------
if (missing(x) || is.null(x)) {
stop("object 'x' not found")
} else if (!missing(x)) {
self$x <- x
}
if (!missing(na.rm)) {
self$na.rm <- na.rm
}
if (na.rm == TRUE) {
self$x <- x[!is.na(x)]
} else if (anyNA(x) & self$na.rm == FALSE) {
stop(
"missing values and NaN's not allowed if 'na.rm' is FALSE"
)
}
# ------------- stop if input x vector is not numeric -------------
if (!is.numeric(x)) {
stop("argument is not a numeric vector")
}
# -------------- check for probs being in range [0,1] -------------
self$eps <- function(...) {100*.Machine$double.eps}
self$epsp1 <- function(...) {1 + 100*.Machine$double.eps}
self$epsm1 <- function(...) {-1 * (100*.Machine$double.eps)}
if (any(
!missing(probs) && (
probs < self$epsm1() | probs > self$epsp1())
)
) {
stop("probs outside [0,1]")
} else if ((
!missing(probs) && (probs <= self$epsp1() & probs >= 1)
)) {
self$probs <- 1
} else if ((
!missing(probs) && (probs >= self$epsm1() & probs <= 0)
)) {
self$probs <- 0
} else if (
(
!missing(probs) && (probs >= 0 & probs <= 1)
)
) {
self$probs <- probs
}
# ------------------- set digits with user input ------------------
if (!missing(digits)) {
self$digits <- digits
}
# ------------------- set type with user input --------------------
if (!missing(type)) {
self$type <- type
}
# ------------------ set names with user input --------------------
if (!missing(names)) {
self$names <- names
}
self$qx() # initialize qx() i.e., sample quantile function
},
# --------- public function qx() i.e., sample quantile function ------
qx = function(...) {
return(
round(
stats::quantile(
self$x,
probs = self$probs,
na.rm = self$na.rm,
type = self$type,
names = self$names
),
digits = self$digits
)
)
}
)
)
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