This function builds a S control chart.
cchart.S(x, type = "n", m = NULL)Return a S control chart.
The exact limits are the alpha/2 and 1-alpha/2 quantiles of the S distribution which is proportional to the square root of a chi-square distribution.
data(softdrink)
#S chart with normalized probability limits
cchart.S(softdrink, type = "n")
#> List of 11
#> $ call : language qcc(data = x, type = "S")
#> $ type : chr "S"
#> $ data.name : chr "x"
#> $ data : num [1:15, 1:10] 2.5 0 1.5 0 0 1 1 0 -2 -0.5 ...
#> ..- attr(*, "dimnames")=List of 2
#> $ statistics: Named num [1:15] 1.333 0.926 1.125 1.174 0.471 ...
#> ..- attr(*, "names")= chr [1:15] "1" "2" "3" "4" ...
#> $ sizes : int [1:15] 10 10 10 10 10 10 10 10 10 10 ...
#> $ center : num 1.09
#> $ std.dev : num 1.12
#> $ nsigmas : num 3
#> $ limits : num [1, 1:2] 0.31 1.88
#> ..- attr(*, "dimnames")=List of 2
#> $ violations:List of 2
#> - attr(*, "class")= chr "qcc"
#S chart with exact probability limits
cchart.S(softdrink, type = "e", 10)
#> List of 11
#> $ call : language qcc(data = x, type = "S", limits = c((sqrt(qchisq(Q_LOWER, m - 1)/(m - 1))) * sd.S(x), (sqrt(qchisq(Q_UPPER,| __truncated__
#> $ type : chr "S"
#> $ data.name : chr "x"
#> $ data : num [1:15, 1:10] 2.5 0 1.5 0 0 1 1 0 -2 -0.5 ...
#> ..- attr(*, "dimnames")=List of 2
#> $ statistics: Named num [1:15] 1.333 0.926 1.125 1.174 0.471 ...
#> ..- attr(*, "names")= chr [1:15] "1" "2" "3" "4" ...
#> $ sizes : int [1:15] 10 10 10 10 10 10 10 10 10 10 ...
#> $ center : num 1.09
#> $ std.dev : num 1.12
#> $ nsigmas : num 3
#> $ limits : num [1, 1:2] 0.417 1.95
#> ..- attr(*, "dimnames")=List of 2
#> $ violations:List of 2
#> - attr(*, "class")= chr "qcc"