This function builds a R control chart.
cchart.R(x, n, type = "norm", y = NULL)Arguments
- x
The data to be plotted.
- n
The sample size.
- type
The type of R chart to be plotted. The options are "norm" (traditional Shewhart R chart) and "tukey" (exact R chart). If not specified, a Shewhart R chart will be plotted.
- y
The data used in phase I to estimate the standard deviation. Required when type = "tukey".
Value
Return a R control chart.
Details
The Shewhart R chart was designed for phase I (at this moment). The limits of the exact R chart are the alpha/2 and 1-alpha/2 quantiles of the R distribution that are calculated as estimated process sd times the quantiles of the relative range (W=R/sigma) distribution.
Examples
data(pistonrings)
attach(pistonrings)
cchart.R(pistonrings[1:25,], 5)
cchart.R(pistonrings[26:40, ], 5, type = "tukey", pistonrings[1:25, ])
#> List of 11
#> $ call : language qcc(data = x, type = "R", limits = c(qtukey(Q_LOWER, n, Inf) * sd.R(y), qtukey(Q_UPPER, n, Inf) * sd.R(y)))
#> $ type : chr "R"
#> $ data.name : chr "x"
#> $ data : num [1:15, 1:5] 74 74 74 74 74 ...
#> ..- attr(*, "dimnames")=List of 2
#> $ statistics: Named num [1:15] 0.044 0.025 0.015 0.019 0.017 ...
#> ..- attr(*, "names")= chr [1:15] "26" "27" "28" "29" ...
#> $ sizes : Named int [1:15] 5 5 5 5 5 5 5 5 5 5 ...
#> ..- attr(*, "names")= chr [1:15] "26" "27" "28" "29" ...
#> $ center : num 0.0245
#> $ std.dev : num 0.0105
#> $ nsigmas : num 3
#> $ limits : num [1, 1:2] 0.00388 0.05262
#> ..- attr(*, "dimnames")=List of 2
#> $ violations:List of 2
#> - attr(*, "class")= chr "qcc"