Like shewhart_xbar_r(), but uses the subgroup standard deviation
(S) instead of the range. Recommended for subgroup sizes greater
than 10, or when subgroup sizes differ.
Arguments
- data
A data frame.
- value
Tidy-eval column reference for the measurement.
- subgroup
Tidy-eval column reference identifying the subgroup (e.g. shift, batch, hour). All subgroups must have equal size. Subgroups are plotted and tested in order of first appearance in
data(time order), not in sorted order of their labels.- sigma_method
One of
"sbar"(default; classical S-bar / c4(n)) or"pooled_sd"(pooled within-subgroup SD; preferred when subgroups have different sizes).- rules
Character vector of rule keys to apply. See
shewhart_rules_available(). Default applies Nelson 1 and 2.- locale
One of
"en","pt","es","fr". Affects plot labels and informative messages.- verbose
Logical. Print progress messages? Defaults to the
shewhart.verboseoption.
Value
A shewhart_chart object of subclass shewhart_xbar_s.
Details
Xbar-chart limits use A3(n); S-chart limits use B3(n) and
B4(n). When sigma_method = "pooled_sd", sigma is estimated as
the pooled within-subgroup standard deviation.
References
Montgomery, D. C. (2019). Introduction to Statistical Quality Control (8th ed.). Wiley. Chapter 6.4.
Examples
set.seed(1)
df <- data.frame(
batch = rep(1:30, each = 12),
y = rnorm(360, mean = 80, sd = 0.6)
)
fit <- shewhart_xbar_s(df, value = y, subgroup = batch)
print(fit)
#>
#> ── Shewhart chart Xbar-S ───────────────────────────────────────────────────────
#> • Observations / subgroups: 30
#> • Phase: "phase_1"
#> • Sigma estimate ("sbar"): 0.5802
#>
#> ── Control limits ──
#>
#> # A tibble: 6 × 3
#> chart line value
#> <chr> <chr> <dbl>
#> 1 Xbar CL 80.0
#> 2 Xbar UCL 80.5
#> 3 Xbar LCL 79.5
#> 4 S CL 0.567
#> 5 S UCL 0.934
#> 6 S LCL 0.201
#> ── Rule violations ──
#>
#> ✔ No violations across 2 rules: "nelson_1_beyond_3s" and "nelson_2_nine_same".