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.
- 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".